| Title: | Mapping the Prevalence of Binary Indicators using Survey Data in Small Areas |
|---|---|
| Description: | Provides a pipeline to perform small area estimation and prevalence mapping of binary indicators using health and demographic survey data, described in Fuglstad et al. (2022) <doi:10.48550/arXiv.2110.09576> and Wakefield et al. (2020) <doi:10.1111/insr.12400>. |
| Authors: | Qianyu Dong [cre, aut], Zehang R Li [aut], Yunhan Wu [aut], Andrea Boskovic [aut], Jon Wakefield [aut] |
| Maintainer: | Qianyu Dong <[email protected]> |
| License: | GPL (>= 2) |
| Version: | 1.0.0 |
| Built: | 2025-01-31 05:33:26 UTC |
| Source: | https://github.com/richardli/surveyprev |
This function get admin information including name, character, population and unban/rural proportion.
adminInfo( poly.adm, by.adm, admin, by.adm.upper = NULL, agg.pop = NULL, proportion = NULL )adminInfo( poly.adm, by.adm, admin, by.adm.upper = NULL, agg.pop = NULL, proportion = NULL )
poly.adm |
spatial polygons dataframe for Admin levels such as Admin 1 or Admin 2. This object can be either an sp::SpatialPolygonsDataFrame object or an sf object. |
by.adm |
the column name of column for Admin names for desired output Admin level, can be such as "NAME_1" or "NAME_2". |
admin |
desired admin level for the output, can be 1 or 2. |
by.adm.upper |
the column name of column for Admin names for upper level of your desired output Admin level when admin=2, can be "NAME_1" when by.adm="NAME_2". |
agg.pop |
data frame of aggregated poplulation from aggPopulation function. It should have two columns: "admin2.name.full" and "population". |
proportion |
data frame of urban/rural proportions. For admin1, is should have two columns: "admin1.name" and "urban". For admin2, it should have three columns: "admin1.name", "admin2.name", and "urban", in order to avoid issues merging datasets with duplicated admin2 names. |
This function returns the 1. dataframe that contains admin 1 and admin 2 information and coordinates for each cluster and 2. Adjacency matrix.
Qianyu Dong
# For sp::SpatialPolygonsDataFrame object data(ZambiaAdm1) class(ZambiaAdm1) info <- adminInfo(poly.adm=ZambiaAdm1, admin = 1, by.adm="NAME_1") data(ZambiaAdm2) class(ZambiaAdm2) info2 <- adminInfo(poly.adm=ZambiaAdm2, admin = 2,by.adm="NAME_2",by.adm.upper="NAME_1") # For sf object geo.sf <- sf::st_as_sf(ZambiaAdm1) info <- adminInfo(poly.adm=geo.sf, admin = 1,by.adm="NAME_1") # To include the population information data(ZambiaPopWomen) info <- adminInfo(poly.adm = ZambiaAdm1, admin = 1,by.adm="NAME_1", agg.pop = ZambiaPopWomen$admin1_pop, proportion = ZambiaPopWomen$admin1_urban )# For sp::SpatialPolygonsDataFrame object data(ZambiaAdm1) class(ZambiaAdm1) info <- adminInfo(poly.adm=ZambiaAdm1, admin = 1, by.adm="NAME_1") data(ZambiaAdm2) class(ZambiaAdm2) info2 <- adminInfo(poly.adm=ZambiaAdm2, admin = 2,by.adm="NAME_2",by.adm.upper="NAME_1") # For sf object geo.sf <- sf::st_as_sf(ZambiaAdm1) info <- adminInfo(poly.adm=geo.sf, admin = 1,by.adm="NAME_1") # To include the population information data(ZambiaPopWomen) info <- adminInfo(poly.adm = ZambiaAdm1, admin = 1,by.adm="NAME_1", agg.pop = ZambiaPopWomen$admin1_pop, proportion = ZambiaPopWomen$admin1_urban )
This function aggregate population to particular admin levels
aggPopulation(tiff, fact = 10, poly.adm, by.adm, by.adm.upper = NULL)aggPopulation(tiff, fact = 10, poly.adm, by.adm, by.adm.upper = NULL)
tiff |
spatial raster of population estimates. |
fact |
factor to aggregate pixels. Default to be 10, i.e., the population estimates will be saved on 1km by 1km grids if the input is 100m by 100m tiff. Larger values of aggregation factor improves the computation speed, but can introduce more errors when the regions defined by the polygon are small in size. |
poly.adm |
spatial polygons dataframe. |
by.adm |
the column name of column for Admin names for desired output Admin level, can be such as "NAME_1" or "NAME_2". Duplicated admin names are handled internally when by.adm.upper is specified |
by.adm.upper |
the column name of column for Admin names for upper level of your desired output Admin level when admin=2, can be "NAME_1" when by.adm="NAME_2". |
This function returns the dataset that contain district name and population for given tiff files and polygons of admin level
Qianyu Dong
## Not run: library(raster) # Download and find total population in age group 0 to 12 months pre <- "https://data.worldpop.org/GIS/AgeSex_structures/" f <- paste0(pre, "Global_2000_2020/2018/ZMB/zmb_f_0_2018.tif") m <- paste0(pre, "Global_2000_2020/2018/ZMB/zmb_m_0_2018.tif") pop_f_0 <- raster(f) pop_m_0 <- raster(m) pop_raster <- pop_f_0 + pop_m_0 # admin1 population agg.pop1 <- aggPopulation( tiff = pop_raster, poly.adm = ZambiaAdm1, by.adm = "NAME_1") # admin2 population agg.pop2 <- aggPopulation( tiff = ZambiaPopWomen_raster, poly.adm = ZambiaAdm2, by.adm = "NAME_2", by.adm.upper="NAME_1") ## End(Not run)## Not run: library(raster) # Download and find total population in age group 0 to 12 months pre <- "https://data.worldpop.org/GIS/AgeSex_structures/" f <- paste0(pre, "Global_2000_2020/2018/ZMB/zmb_f_0_2018.tif") m <- paste0(pre, "Global_2000_2020/2018/ZMB/zmb_m_0_2018.tif") pop_f_0 <- raster(f) pop_m_0 <- raster(m) pop_raster <- pop_f_0 + pop_m_0 # admin1 population agg.pop1 <- aggPopulation( tiff = pop_raster, poly.adm = ZambiaAdm1, by.adm = "NAME_1") # admin2 population agg.pop2 <- aggPopulation( tiff = ZambiaPopWomen_raster, poly.adm = ZambiaAdm2, by.adm = "NAME_2", by.adm.upper="NAME_1") ## End(Not run)
This function aggregate survey weight to particular admin levels
aggSurveyWeight( data, cluster.info, admin, poly.adm = NULL, by.adm = NULL, by.adm.upper = NULL )aggSurveyWeight( data, cluster.info, admin, poly.adm = NULL, by.adm = NULL, by.adm.upper = NULL )
data |
dataframe that contains the indicator of interests, output of getDHSindicator function |
cluster.info |
list that contains admin 1 and admin 2 information and coordinates for each cluster, output of clusterinfo function |
admin |
desired admin level for aggregation |
poly.adm |
spatial polygons dataframe |
by.adm |
the column name of column for Admin names for desired output Admin level, can be such as "NAME_1" or "NAME_2". |
by.adm.upper |
the column name of column for Admin names for upper level of your desired output Admin level when admin=2, can be "NAME_1" when by.adm="NAME_2". |
This function returns the dataset that contain admin name and survey weight.
Qianyu Dong
## Not run: # admin1 population year <- 2018 country <- "Zambia" indicator="nmr" geo <- getDHSgeo(country = country, year = year) dhsData <- getDHSdata(country = country, indicator=indicator, year = year) data<- getDHSindicator(dhsData, indicator = indicator) poly.adm1=ZambiaAdm1 poly.adm2=ZambiaAdm2 cluster.info<-clusterInfo(geo=geo, poly.adm1=poly.adm1, poly.adm2=poly.adm2, by.adm1 = "NAME_1",by.adm2 = "NAME_2") agg.survey1<-aggSurveyWeight(data=data,cluster.info=cluster.info,admin=1) agg.survey2<-aggSurveyWeight(data=data,cluster.info=cluster.info,admin=2, poly.adm = poly.adm2, by.adm="NAME_2", by.adm.upper ="NAME_1") ## End(Not run)## Not run: # admin1 population year <- 2018 country <- "Zambia" indicator="nmr" geo <- getDHSgeo(country = country, year = year) dhsData <- getDHSdata(country = country, indicator=indicator, year = year) data<- getDHSindicator(dhsData, indicator = indicator) poly.adm1=ZambiaAdm1 poly.adm2=ZambiaAdm2 cluster.info<-clusterInfo(geo=geo, poly.adm1=poly.adm1, poly.adm2=poly.adm2, by.adm1 = "NAME_1",by.adm2 = "NAME_2") agg.survey1<-aggSurveyWeight(data=data,cluster.info=cluster.info,admin=1) agg.survey2<-aggSurveyWeight(data=data,cluster.info=cluster.info,admin=2, poly.adm = poly.adm2, by.adm="NAME_2", by.adm.upper ="NAME_1") ## End(Not run)
AH_TOBC_W_OTH
AH_TOBC_W_OTH(IRdata)AH_TOBC_W_OTH(IRdata)
IRdata |
data.frame from survryPrev::getDHSdata |
A partially processed data.frame that will be used in survryPrev::getDHSindicator. The whole function can be used as a parameter in survryPrev::getDHSindicator
Miaolei Bao, Yunhan Wu, Qianyu Dong
AH_TOBU_M_ASM
AH_TOBU_M_ASM(MRdata)AH_TOBU_M_ASM(MRdata)
MRdata |
data.frame from survryPrev::getDHSdata |
A partially processed data.frame that will be used in survryPrev::getDHSindicator. The whole function can be used as a parameter in survryPrev::getDHSindicator
Miaolei Bao, Yunhan Wu, Qianyu Dong
AH_TOBU_M_SNN
AH_TOBU_M_SNN(MRdata)AH_TOBU_M_SNN(MRdata)
MRdata |
data.frame from survryPrev::getDHSdata |
A partially processed data.frame that will be used in survryPrev::getDHSindicator. The whole function can be used as a parameter in survryPrev::getDHSindicator
Miaolei Bao, Yunhan Wu, Qianyu Dong
AH_TOBU_W_SNM
AH_TOBU_W_SNM(IRdata)AH_TOBU_W_SNM(IRdata)
IRdata |
data.frame from survryPrev::getDHSdata |
A partially processed data.frame that will be used in survryPrev::getDHSindicator. The whole function can be used as a parameter in survryPrev::getDHSindicator
Miaolei Bao, Yunhan Wu, Qianyu Dong
AH_TOBU_W_SNN
AH_TOBU_W_SNN(IRdata)AH_TOBU_W_SNN(IRdata)
IRdata |
data.frame from survryPrev::getDHSdata |
A partially processed data.frame that will be used in survryPrev::getDHSindicator. The whole function can be used as a parameter in survryPrev::getDHSindicator
Miaolei Bao, Yunhan Wu, Qianyu Dong
AN_NUTS_W_OVW Women who are overweight according to BMI (25.0-29.9) nt_wm_ovwt in github IR
AN_NUTS_W_OVW(Rdata)AN_NUTS_W_OVW(Rdata)
Rdata |
data.frame from survryPrev::getDHSdata |
A partially processed data.frame that will be used in survryPrev::getDHSindicator. The whole function can be used as a parameter in survryPrev::getDHSindicator
Miaolei Bao, Yunhan Wu, Qianyu Dong
CH_VACS_C_BAS Children with all 8 basic vaccinations (age 12-23) "All basic vaccinations according to either source"
ch_allvac_either(Rdata)ch_allvac_either(Rdata)
Rdata |
data.frame from survryPrev::getDHSdata |
A partially processed data.frame that will be used in survryPrev::getDHSindicator. The whole function can be used as a parameter in survryPrev::getDHSindicator
Qianyu Dong
## Not run: dhsData <- getDHSdata(country = "Zambia", indicator = "CH_VACS_C_BAS", year = 2018) data <- getDHSindicator(dhsData, indicator = NULL, FUN = surveyPrev::ch_allvac_either) ## End(Not run)## Not run: dhsData <- getDHSdata(country = "Zambia", indicator = "CH_VACS_C_BAS", year = 2018) data <- getDHSindicator(dhsData, indicator = NULL, FUN = surveyPrev::ch_allvac_either) ## End(Not run)
CH_ARIS_C_ADV Children with ARI for whom advice or treatment was sought; ch_ari_care in github KR
CH_ARIS_C_ADV(Rdata)CH_ARIS_C_ADV(Rdata)
Rdata |
data.frame from survryPrev::getDHSdata |
A partially processed data.frame that will be used in survryPrev::getDHSindicator. The whole function can be used as a parameter in survryPrev::getDHSindicator
Miaolei Bao, Yunhan Wu, Qianyu Dong
CH_DIAT_C_ORT KR Diarrhea treatment (Children under five with diarrhea treated with either ORS or RHF)
ch_diar_ors_rhf(Rdata)ch_diar_ors_rhf(Rdata)
Rdata |
data.frame from survryPrev::getDHSdata |
A partially processed data.frame that will be used in survryPrev::getDHSindicator. The whole function can be used as a parameter in survryPrev::getDHSindicator
Qianyu Dong
## Not run: dhsData <- getDHSdata(country = "Zambia", indicator = "CH_DIAT_C_ORT", year = 2018) data <- getDHSindicator(dhsData, indicator = NULL, FUN = surveyPrev::ch_diar_ors_rhf) ## End(Not run)## Not run: dhsData <- getDHSdata(country = "Zambia", indicator = "CH_DIAT_C_ORT", year = 2018) data <- getDHSindicator(dhsData, indicator = NULL, FUN = surveyPrev::ch_diar_ors_rhf) ## End(Not run)
CH_DIAT_C_ABI
CH_DIAT_C_ABI(KRdata)CH_DIAT_C_ABI(KRdata)
KRdata |
data.frame from survryPrev::getDHSdata |
A partially processed data.frame that will be used in survryPrev::getDHSindicator. The whole function can be used as a parameter in survryPrev::getDHSindicator
Miaolei Bao, Yunhan Wu, Qianyu Dong
CH_DIAT_C_ADV Treatment of diarrhea: Advice or treatment was sought; ch_diar_care in github KR
CH_DIAT_C_ADV(Rdata)CH_DIAT_C_ADV(Rdata)
Rdata |
data.frame from survryPrev::getDHSdata |
A partially processed data.frame that will be used in survryPrev::getDHSindicator. The whole function can be used as a parameter in survryPrev::getDHSindicator
Miaolei Bao, Yunhan Wu, Qianyu Dong
CH_DIAT_C_AMO
CH_DIAT_C_AMO(KRdata)CH_DIAT_C_AMO(KRdata)
KRdata |
data.frame from survryPrev::getDHSdata |
A partially processed data.frame that will be used in survryPrev::getDHSindicator. The whole function can be used as a parameter in survryPrev::getDHSindicator
Miaolei Bao, Yunhan Wu, Qianyu Dong
CH_DIAT_C_NOT
CH_DIAT_C_NOT(KRdata)CH_DIAT_C_NOT(KRdata)
KRdata |
data.frame from survryPrev::getDHSdata |
A partially processed data.frame that will be used in survryPrev::getDHSindicator. The whole function can be used as a parameter in survryPrev::getDHSindicator
Miaolei Bao, Yunhan Wu, Qianyu Dong
CH_DIAT_C_ORS
CH_DIAT_C_ORS(KRdata)CH_DIAT_C_ORS(KRdata)
KRdata |
data.frame from survryPrev::getDHSdata |
A partially processed data.frame that will be used in survryPrev::getDHSindicator. The whole function can be used as a parameter in survryPrev::getDHSindicator
Miaolei Bao, Yunhan Wu, Qianyu Dong
CH_DIAT_C_ORT
CH_DIAT_C_ORT(KRdata)CH_DIAT_C_ORT(KRdata)
KRdata |
data.frame from survryPrev::getDHSdata |
A partially processed data.frame that will be used in survryPrev::getDHSindicator. The whole function can be used as a parameter in survryPrev::getDHSindicator
Miaolei Bao, Yunhan Wu, Qianyu Dong
CH_DIAT_C_OSI
CH_DIAT_C_OSI(KRdata)CH_DIAT_C_OSI(KRdata)
KRdata |
data.frame from survryPrev::getDHSdata |
A partially processed data.frame that will be used in survryPrev::getDHSindicator. The whole function can be used as a parameter in survryPrev::getDHSindicator
Miaolei Bao, Yunhan Wu, Qianyu Dong
CH_DIAT_C_RHF
CH_DIAT_C_RHF(KRdata)CH_DIAT_C_RHF(KRdata)
KRdata |
data.frame from survryPrev::getDHSdata |
A partially processed data.frame that will be used in survryPrev::getDHSindicator. The whole function can be used as a parameter in survryPrev::getDHSindicator
Miaolei Bao, Yunhan Wu, Qianyu Dong
CH_DIFP_C_FAL
CH_DIFP_C_FAL(KRdata)CH_DIFP_C_FAL(KRdata)
KRdata |
data.frame from survryPrev::getDHSdata |
A partially processed data.frame that will be used in survryPrev::getDHSindicator. The whole function can be used as a parameter in survryPrev::getDHSindicator
Miaolei Bao, Yunhan Wu, Qianyu Dong
CH_FEVR_C_FEV
CH_FEVR_C_FEV(KRdata)CH_FEVR_C_FEV(KRdata)
KRdata |
data.frame from survryPrev::getDHSdata |
A partially processed data.frame that will be used in survryPrev::getDHSindicator. The whole function can be used as a parameter in survryPrev::getDHSindicator
Miaolei Bao, Yunhan Wu, Qianyu Dong
CH_FEVT_C_ADV Children with fever for whom advice or treatment was sought ch_fev_care in github ml_fev_care should produce the same data KR
CH_FEVT_C_ADV(Rdata)CH_FEVT_C_ADV(Rdata)
Rdata |
data.frame from survryPrev::getDHSdata |
A partially processed data.frame that will be used in survryPrev::getDHSindicator. The whole function can be used as a parameter in survryPrev::getDHSindicator
Miaolei Bao, Yunhan Wu, Qianyu Dong
CH_VACC_C_MSL MCV: Measles Measles vaccination received Percentage of children (age 12-23) ch_meas_either CH_VAC.do KR "Measles vaccination according to either source"
ch_meas_either(Rdata)ch_meas_either(Rdata)
Rdata |
data.frame from survryPrev::getDHSdata |
A partially processed data.frame that will be used in survryPrev::getDHSindicator. The whole function can be used as a parameter in survryPrev::getDHSindicator
Qianyu Dong
## Not run: dhsData <- getDHSdata(country = "Zambia", indicator = "CH_VACC_C_MSL", year = 2018) data <- getDHSindicator(dhsData, indicator = NULL, FUN = surveyPrev::ch_meas_either) ## End(Not run)## Not run: dhsData <- getDHSdata(country = "Zambia", indicator = "CH_VACC_C_MSL", year = 2018) data <- getDHSindicator(dhsData, indicator = NULL, FUN = surveyPrev::ch_meas_either) ## End(Not run)
CH_VACS_C_NON KR Children with no vaccinations (age 12-23)
ch_novac_either(Rdata)ch_novac_either(Rdata)
Rdata |
data.frame from survryPrev::getDHSdata |
A partially processed data.frame that will be used in survryPrev::getDHSindicator. The whole function can be used as a parameter in survryPrev::getDHSindicator
Qianyu Dong
## Not run: dhsData <- getDHSdata(country = "Zambia", indicator = "CH_VACS_C_NON", year = 2018) data <- getDHSindicator(dhsData, indicator = NULL, FUN = surveyPrev::ch_novac_either) ## End(Not run)## Not run: dhsData <- getDHSdata(country = "Zambia", indicator = "CH_VACS_C_NON", year = 2018) data <- getDHSindicator(dhsData, indicator = NULL, FUN = surveyPrev::ch_novac_either) ## End(Not run)
CH_VACC_C_DP1 KR Percentage of children (age 12-23) Pentavalent 1rd dose vaccination according to either source"
ch_pent1_either(Rdata)ch_pent1_either(Rdata)
Rdata |
data.frame from survryPrev::getDHSdata |
A partially processed data.frame that will be used in survryPrev::getDHSindicator. The whole function can be used as a parameter in survryPrev::getDHSindicator
Qianyu Dong
## Not run: dhsData <- getDHSdata(country = "Zambia", indicator = "CH_VACC_C_DP1", year = 2018) data <- getDHSindicator(dhsData, indicator = NULL, FUN = surveyPrev::ch_pent1_either) ## End(Not run)## Not run: dhsData <- getDHSdata(country = "Zambia", indicator = "CH_VACC_C_DP1", year = 2018) data <- getDHSindicator(dhsData, indicator = NULL, FUN = surveyPrev::ch_pent1_either) ## End(Not run)
CH_VACC_C_DP3 DPT3 KR Percentage of children (age 12-23) Pentavalent 3rd dose vaccination according to either source"
ch_pent3_either(Rdata)ch_pent3_either(Rdata)
Rdata |
data.frame from survryPrev::getDHSdata |
A partially processed data.frame that will be used in survryPrev::getDHSindicator. The whole function can be used as a parameter in survryPrev::getDHSindicator
Qianyu Dong
## Not run: dhsData <- getDHSdata(country = "Zambia", indicator = "CH_VACC_C_DP3", year = 2018) data <- getDHSindicator(dhsData, indicator = NULL, FUN = surveyPrev::ch_pent3_either) ## End(Not run)## Not run: dhsData <- getDHSdata(country = "Zambia", indicator = "CH_VACC_C_DP3", year = 2018) data <- getDHSindicator(dhsData, indicator = NULL, FUN = surveyPrev::ch_pent3_either) ## End(Not run)
CH_SZWT_C_L25
CH_SZWT_C_L25(KRdata)CH_SZWT_C_L25(KRdata)
KRdata |
data.frame from survryPrev::getDHSdata |
A partially processed data.frame that will be used in survryPrev::getDHSindicator. The whole function can be used as a parameter in survryPrev::getDHSindicator
Miaolei Bao, Yunhan Wu, Qianyu Dong
CH_VACC_C_BCG Percentage of children 12-23 months who had received BCG vaccination ms_afm_15 in github KR
CH_VACC_C_BCG(Rdata)CH_VACC_C_BCG(Rdata)
Rdata |
data.frame from survryPrev::getDHSdata |
A partially processed data.frame that will be used in survryPrev::getDHSindicator. The whole function can be used as a parameter in survryPrev::getDHSindicator
Miaolei Bao, Yunhan Wu, Qianyu Dong
This function add admin 1 and admin2 information to a paticular DHS survey.
clusterInfo(geo, poly.adm1, poly.adm2, by.adm1 = "NAME_1", by.adm2 = "NAME_2")clusterInfo(geo, poly.adm1, poly.adm2, by.adm1 = "NAME_1", by.adm2 = "NAME_2")
geo |
spatial point dataframe |
poly.adm1 |
spatial polygons dataframe for admin 1 |
poly.adm2 |
spatial polygons dataframe for admin 2 or other lower admin level. |
by.adm1 |
the column name of column for Admin names for admin 1 |
by.adm2 |
the column name of column for Admin names for admin 2 or other lower admin level. |
This function returns the dataset that contains admin 1 and admin 2 information and coordinates for each cluster.
Qianyu Dong
## Not run: geo <- getDHSgeo(country = "Zambia", year = 2018) data(ZambiaAdm1) data(ZambiaAdm2) cluster.info <- clusterInfo(geo = geo, poly.adm1 = ZambiaAdm1, poly.adm2 = ZambiaAdm2) ## End(Not run)## Not run: geo <- getDHSgeo(country = "Zambia", year = 2018) data(ZambiaAdm1) data(ZambiaAdm2) cluster.info <- clusterInfo(geo = geo, poly.adm1 = ZambiaAdm1, poly.adm2 = ZambiaAdm2) ## End(Not run)
This function calculate smoothed direct estimates at given admin level.
clusterModel( data, cluster.info, admin.info, X = NULL, admin, CI = 0.95, model = c("bym2", "iid"), stratification = FALSE, aggregation = FALSE, nested = FALSE, overdisp.mean = 0, overdisp.prec = 0.4, pc.u = 1, pc.alpha = 0.01, pc.u.phi = 0.5, pc.alpha.phi = 2/3 )clusterModel( data, cluster.info, admin.info, X = NULL, admin, CI = 0.95, model = c("bym2", "iid"), stratification = FALSE, aggregation = FALSE, nested = FALSE, overdisp.mean = 0, overdisp.prec = 0.4, pc.u = 1, pc.alpha = 0.01, pc.u.phi = 0.5, pc.alpha.phi = 2/3 )
data |
dataframe that contains the indicator of interests(column name is value), output of getDHSindicator function |
cluster.info |
dataframe that contains admin 1 and admin 2 information and coordinates for each cluster. |
admin.info |
dataframe that contains population and urban/rural proportion at specific admin level |
X |
dataframe that contains areal covariates, the first column should be the same admin name as in admin.info$data. |
admin |
admin level for the model |
CI |
Credible interval to be used. Default to 0.95. |
model |
smoothing model used in the random effect. Options are independent ("iid") or spatial ("bym2"). |
stratification |
whether or not to include urban/rural stratum. |
aggregation |
whether or not report aggregation results. |
nested |
whether or not to fit a nested model. |
overdisp.mean |
prior mean for logit(d), where d is the intracluster correlation. |
overdisp.prec |
prior precision for logit(d), where d is the intracluster correlation. |
pc.u |
pc prior u for iid or bym2 precision. |
pc.alpha |
pc prior alpha for iid or bym2 precision. |
pc.u.phi |
pc prior u for bym2 mixing paramete. |
pc.alpha.phi |
pc prior u for bym2 mixing paramete. |
This function returns the dataset that contain district name and population for given tiff files and polygons of admin level,
Qianyu Dong
## Not run: geo <- getDHSgeo(country = "Zambia", year = 2018) data(ZambiaAdm1) data(ZambiaAdm2) data(ZambiaPopWomen) cluster.info <- clusterInfo(geo = geo, poly.adm1 = ZambiaAdm1, poly.adm2 = ZambiaAdm2) dhsData <- getDHSdata(country = "Zambia", indicator = "ancvisit4+", year = 2018) data <- getDHSindicator(dhsData, indicator = "ancvisit4") admin.info1 <- adminInfo(poly.adm = ZambiaAdm1, admin = 1, agg.pop =ZambiaPopWomen$admin1_pop, proportion = ZambiaPopWomen$admin1_urban) cl_res_ad1 <- clusterModel(data=data, cluster.info = cluster.info, admin.info = admin.info1, stratification = FALSE, model = "bym2", admin = 1, aggregation = TRUE, CI = 0.95) cl_res_ad1$res.admin1 # compare with the DHS direct estimates dhs_table <- get_api_table(country = "ZM", survey = "ZM2018DHS", indicator = "RH_ANCN_W_N4P", simplify = TRUE) subset(dhs_table, ByVariableLabel == "Five years preceding the survey") ## End(Not run)## Not run: geo <- getDHSgeo(country = "Zambia", year = 2018) data(ZambiaAdm1) data(ZambiaAdm2) data(ZambiaPopWomen) cluster.info <- clusterInfo(geo = geo, poly.adm1 = ZambiaAdm1, poly.adm2 = ZambiaAdm2) dhsData <- getDHSdata(country = "Zambia", indicator = "ancvisit4+", year = 2018) data <- getDHSindicator(dhsData, indicator = "ancvisit4") admin.info1 <- adminInfo(poly.adm = ZambiaAdm1, admin = 1, agg.pop =ZambiaPopWomen$admin1_pop, proportion = ZambiaPopWomen$admin1_urban) cl_res_ad1 <- clusterModel(data=data, cluster.info = cluster.info, admin.info = admin.info1, stratification = FALSE, model = "bym2", admin = 1, aggregation = TRUE, CI = 0.95) cl_res_ad1$res.admin1 # compare with the DHS direct estimates dhs_table <- get_api_table(country = "ZM", survey = "ZM2018DHS", indicator = "RH_ANCN_W_N4P", simplify = TRUE) subset(dhs_table, ByVariableLabel == "Five years preceding the survey") ## End(Not run)
BR
CM_ECMR_C_NNF(Rdata)CM_ECMR_C_NNF(Rdata)
Rdata |
data.frame from survryPrev::getDHSdata |
A partially processed data.frame that will be used in survryPrev::getDHSindicator. The whole function can be used as a parameter in survryPrev::getDHSindicator
Miaolei Bao, Yunhan Wu, Qianyu Dong
CN_BRFI_C_EVR
CN_BRFI_C_EVR(KRdata)CN_BRFI_C_EVR(KRdata)
KRdata |
data.frame from survryPrev::getDHSdata |
A partially processed data.frame that will be used in survryPrev::getDHSindicator. The whole function can be used as a parameter in survryPrev::getDHSindicator
Miaolei Bao, Yunhan Wu, Qianyu Dong
CN_IYCF_C_4FA Percentage of children age 6-23 months fed five or more food groups. The food groups are a. breastmilk b. infant formula, milk other than breast milk, cheese or yogurt or other milk products; c. foods made from grains, roots, and tubers, including porridge and fortified baby food from grains; d. vitamin A-rich fruits and vegetables (and red palm oil); e. other fruits and vegetables; f. eggs; g. meat, poultry, fish, and shellfish (and organ meats); h. legumes and nuts. nt_mdd in github KR
CN_IYCF_C_4FA(Rdata)CN_IYCF_C_4FA(Rdata)
Rdata |
data.frame from survryPrev::getDHSdata |
A partially processed data.frame that will be used in survryPrev::getDHSindicator. The whole function can be used as a parameter in survryPrev::getDHSindicator
Miaolei Bao, Yunhan Wu, Qianyu Dong
CN_NUTS_C_HA2
CN_NUTS_C_HA2(PRdata)CN_NUTS_C_HA2(PRdata)
PRdata |
data.frame from survryPrev::getDHSdata |
A partially processed data.frame that will be used in survryPrev::getDHSindicator. The whole function can be used as a parameter in survryPrev::getDHSindicator
Miaolei Bao, Yunhan Wu, Qianyu Dong
CN_NUTS_C_HA3
CN_NUTS_C_HA3(PRdata)CN_NUTS_C_HA3(PRdata)
PRdata |
data.frame from survryPrev::getDHSdata |
A partially processed data.frame that will be used in survryPrev::getDHSindicator. The whole function can be used as a parameter in survryPrev::getDHSindicator
Miaolei Bao, Yunhan Wu, Qianyu Dong
CN_NUTS_C_WA2
CN_NUTS_C_WA2(PRdata)CN_NUTS_C_WA2(PRdata)
PRdata |
data.frame from survryPrev::getDHSdata |
A partially processed data.frame that will be used in survryPrev::getDHSindicator. The whole function can be used as a parameter in survryPrev::getDHSindicator
Miaolei Bao, Yunhan Wu, Qianyu Dong
CN_NUTS_C_WA3
CN_NUTS_C_WA3(PRdata)CN_NUTS_C_WA3(PRdata)
PRdata |
data.frame from survryPrev::getDHSdata |
A partially processed data.frame that will be used in survryPrev::getDHSindicator. The whole function can be used as a parameter in survryPrev::getDHSindicator
Miaolei Bao, Yunhan Wu, Qianyu Dong
CN_NUTS_C_WAP
CN_NUTS_C_WAP(PRdata)CN_NUTS_C_WAP(PRdata)
PRdata |
data.frame from survryPrev::getDHSdata |
A partially processed data.frame that will be used in survryPrev::getDHSindicator. The whole function can be used as a parameter in survryPrev::getDHSindicator
Miaolei Bao, Yunhan Wu, Qianyu Dong
CN_NUTS_C_WH2
CN_NUTS_C_WH2(PRdata)CN_NUTS_C_WH2(PRdata)
PRdata |
data.frame from survryPrev::getDHSdata |
A partially processed data.frame that will be used in survryPrev::getDHSindicator. The whole function can be used as a parameter in survryPrev::getDHSindicator
Miaolei Bao, Yunhan Wu, Qianyu Dong
CN_NUTS_C_WH3
CN_NUTS_C_WH3(PRdata)CN_NUTS_C_WH3(PRdata)
PRdata |
data.frame from survryPrev::getDHSdata |
A partially processed data.frame that will be used in survryPrev::getDHSindicator. The whole function can be used as a parameter in survryPrev::getDHSindicator
Miaolei Bao, Yunhan Wu, Qianyu Dong
CN_NUTS_C_WHP
CN_NUTS_C_WHP(PRdata)CN_NUTS_C_WHP(PRdata)
PRdata |
data.frame from survryPrev::getDHSdata |
A partially processed data.frame that will be used in survryPrev::getDHSindicator. The whole function can be used as a parameter in survryPrev::getDHSindicator
Miaolei Bao, Yunhan Wu, Qianyu Dong
CO_INUS_W_EVU
CO_INUS_W_EVU(IRdata)CO_INUS_W_EVU(IRdata)
IRdata |
data.frame from survryPrev::getDHSdata |
A partially processed data.frame that will be used in survryPrev::getDHSindicator. The whole function can be used as a parameter in survryPrev::getDHSindicator
Miaolei Bao, Yunhan Wu, Qianyu Dong
CO_INUS_W_U12
CO_INUS_W_U12(IRdata)CO_INUS_W_U12(IRdata)
IRdata |
data.frame from survryPrev::getDHSdata |
A partially processed data.frame that will be used in survryPrev::getDHSindicator. The whole function can be used as a parameter in survryPrev::getDHSindicator
Miaolei Bao, Yunhan Wu, Qianyu Dong
CO_MOBB_W_BNK
CO_MOBB_W_BNK(IRdata)CO_MOBB_W_BNK(IRdata)
IRdata |
data.frame from survryPrev::getDHSdata |
A partially processed data.frame that will be used in survryPrev::getDHSindicator. The whole function can be used as a parameter in survryPrev::getDHSindicator
Miaolei Bao, Yunhan Wu, Qianyu Dong
CO_MOBB_W_MBF
CO_MOBB_W_MBF(IRdata)CO_MOBB_W_MBF(IRdata)
IRdata |
data.frame from survryPrev::getDHSdata |
A partially processed data.frame that will be used in survryPrev::getDHSindicator. The whole function can be used as a parameter in survryPrev::getDHSindicator
Miaolei Bao, Yunhan Wu, Qianyu Dong
CO_MOBB_W_MOB
CO_MOBB_W_MOB(IRdata)CO_MOBB_W_MOB(IRdata)
IRdata |
data.frame from survryPrev::getDHSdata |
A partially processed data.frame that will be used in survryPrev::getDHSindicator. The whole function can be used as a parameter in survryPrev::getDHSindicator
Miaolei Bao, Yunhan Wu, Qianyu Dong
CP_BREG_C_CRT
CP_BREG_C_CRT(PRdata)CP_BREG_C_CRT(PRdata)
PRdata |
data.frame from survryPrev::getDHSdata |
A partially processed data.frame that will be used in survryPrev::getDHSindicator. The whole function can be used as a parameter in survryPrev::getDHSindicator
Miaolei Bao, Yunhan Wu, Qianyu Dong
CP_BREG_C_NCT
CP_BREG_C_NCT(PRdata)CP_BREG_C_NCT(PRdata)
PRdata |
data.frame from survryPrev::getDHSdata |
A partially processed data.frame that will be used in survryPrev::getDHSindicator. The whole function can be used as a parameter in survryPrev::getDHSindicator
Miaolei Bao, Yunhan Wu, Qianyu Dong
CP_BREG_C_REG
CP_BREG_C_REG(PRdata)CP_BREG_C_REG(PRdata)
PRdata |
data.frame from survryPrev::getDHSdata |
A partially processed data.frame that will be used in survryPrev::getDHSindicator. The whole function can be used as a parameter in survryPrev::getDHSindicator
Miaolei Bao, Yunhan Wu, Qianyu Dong
This function calculate direct estimates at given admin level.
directEST( data, cluster.info, admin, strata = "all", CI = 0.95, weight = c("population", "survey")[1], admin.info = NULL, aggregation = FALSE, alt.strata = NULL, ... )directEST( data, cluster.info, admin, strata = "all", CI = 0.95, weight = c("population", "survey")[1], admin.info = NULL, aggregation = FALSE, alt.strata = NULL, ... )
data |
dataframe that contains the indicator of interests, output of getDHSindicator function |
cluster.info |
list contains data and wrong.points. data contains admin 1 and admin 2 information and coordinates for each cluster. wrong.points. contains cluster id for cluster without coordinates or admin 1 information. Output of getDHSindicator function |
admin |
admin level for the model. |
strata |
use only urban or rural data, only for national level model |
CI |
Credible interval to be used. Default to 0.95. |
weight |
the weight used for aggregating result, "population" or "survey" |
admin.info |
list contains data and mat, data contains population and urban/rural proportion at specific admin level and mat is the adjacency matrix, output of adminInfo function |
aggregation |
whether or not report aggregation results. |
alt.strata |
the variable name in the data frame that correspond to the stratification variable. Most of the DHS surveys are stratified by admin 1 area crossed with urban/rural, which is the default stratification variable created by the function (when |
... |
Additional arguments passed on to the 'smoothSurvey' function |
This function returns the dataset that contain district name and population for given tiff files and polygons of admin level,
Qianyu Dong
## Not run: ## ## Direct estimation of ANC visit 4+ proportion ## geo <- getDHSgeo(country = "Zambia", year = 2018) data(ZambiaAdm1) data(ZambiaAdm2) data(ZambiaPopWomen) cluster.info<-clusterInfo(geo=geo, poly.adm1=ZambiaAdm1, poly.adm2=ZambiaAdm2, by.adm1 = "NAME_1",by.adm2 = "NAME_2") dhsData <- getDHSdata(country = "Zambia", indicator = "ancvisit4+", year = 2018) data <- getDHSindicator(dhsData, indicator = "ancvisit4+") res_ad1 <- directEST(data = data, cluster.info = cluster.info, admin = 1, aggregation = FALSE) res_ad1 # compare with the DHS direct estimates dhs_table <- get_api_table(country = "ZM", survey = "ZM2018DHS", indicator = "RH_ANCN_W_N4P", simplify = TRUE) subset(dhs_table, ByVariableLabel == "Five years preceding the survey") ## ## Changing customized stratification variable ## data_alt <- data # Assuming the stratification is done with only admin1 area # and not stratified by urban and rural # Note that this is not the correct stratification, but we use # this as an illustration to create user-specified strata variable data_alt$new_strata <- data_alt$v024 res_ad1_wrong <- directEST(data = data_alt, cluster.info = cluster.info, admin = 1, aggregation = FALSE, alt.strata = "new_strata") res_ad1_wrong ## End(Not run)## Not run: ## ## Direct estimation of ANC visit 4+ proportion ## geo <- getDHSgeo(country = "Zambia", year = 2018) data(ZambiaAdm1) data(ZambiaAdm2) data(ZambiaPopWomen) cluster.info<-clusterInfo(geo=geo, poly.adm1=ZambiaAdm1, poly.adm2=ZambiaAdm2, by.adm1 = "NAME_1",by.adm2 = "NAME_2") dhsData <- getDHSdata(country = "Zambia", indicator = "ancvisit4+", year = 2018) data <- getDHSindicator(dhsData, indicator = "ancvisit4+") res_ad1 <- directEST(data = data, cluster.info = cluster.info, admin = 1, aggregation = FALSE) res_ad1 # compare with the DHS direct estimates dhs_table <- get_api_table(country = "ZM", survey = "ZM2018DHS", indicator = "RH_ANCN_W_N4P", simplify = TRUE) subset(dhs_table, ByVariableLabel == "Five years preceding the survey") ## ## Changing customized stratification variable ## data_alt <- data # Assuming the stratification is done with only admin1 area # and not stratified by urban and rural # Note that this is not the correct stratification, but we use # this as an illustration to create user-specified strata variable data_alt$new_strata <- data_alt$v024 res_ad1_wrong <- directEST(data = data_alt, cluster.info = cluster.info, admin = 1, aggregation = FALSE, alt.strata = "new_strata") res_ad1_wrong ## End(Not run)
DV_AFSV_W_A10
DV_AFSV_W_A10(IRdata)DV_AFSV_W_A10(IRdata)
IRdata |
data.frame from survryPrev::getDHSdata |
A partially processed data.frame that will be used in survryPrev::getDHSindicator. The whole function can be used as a parameter in survryPrev::getDHSindicator
A partially processed data.frame that will be used in survryPrev::getDHSindicator. The whole function can be used as a parameter in survryPrev::getDHSindicator
Miaolei Bao, Yunhan Wu, Qianyu Dong
DV_AFSV_W_A12
DV_AFSV_W_A12(IRdata)DV_AFSV_W_A12(IRdata)
IRdata |
data.frame from survryPrev::getDHSdata |
A partially processed data.frame that will be used in survryPrev::getDHSindicator. The whole function can be used as a parameter in survryPrev::getDHSindicator
A partially processed data.frame that will be used in survryPrev::getDHSindicator. The whole function can be used as a parameter in survryPrev::getDHSindicator
Miaolei Bao, Yunhan Wu, Qianyu Dong
DV_EXPV_W_12M Percentage of women who have experienced physical violence in the past 12 months often or sometimes dv_phy_12m in github IR
DV_EXPV_W_12M(Rdata)DV_EXPV_W_12M(Rdata)
Rdata |
data.frame from survryPrev::getDHSdata |
A partially processed data.frame that will be used in survryPrev::getDHSindicator. The whole function can be used as a parameter in survryPrev::getDHSindicator
Miaolei Bao, Yunhan Wu, Qianyu Dong
DV_EXSV_W_12M Percentage of women who ever experienced sexual violence dv_sex_12m in github IR
DV_EXSV_W_12M(Rdata)DV_EXSV_W_12M(Rdata)
Rdata |
data.frame from survryPrev::getDHSdata |
A partially processed data.frame that will be used in survryPrev::getDHSindicator. The whole function can be used as a parameter in survryPrev::getDHSindicator
Miaolei Bao, Yunhan Wu, Qianyu Dong
DV_EXSV_W_EVR Percentage of women who ever experienced sexual violence dv_sex in github IR
DV_EXSV_W_EVR(Rdata)DV_EXSV_W_EVR(Rdata)
Rdata |
data.frame from survryPrev::getDHSdata |
A partially processed data.frame that will be used in survryPrev::getDHSindicator. The whole function can be used as a parameter in survryPrev::getDHSindicator
Miaolei Bao, Yunhan Wu, Qianyu Dong
DV_PCPV_W_CBF
DV_PCPV_W_CBF(IRdata)DV_PCPV_W_CBF(IRdata)
IRdata |
data.frame from survryPrev::getDHSdata |
A partially processed data.frame that will be used in survryPrev::getDHSindicator. The whole function can be used as a parameter in survryPrev::getDHSindicator
Miaolei Bao, Yunhan Wu, Qianyu Dong
DV_PCPV_W_CHD
DV_PCPV_W_CHD(IRdata)DV_PCPV_W_CHD(IRdata)
IRdata |
data.frame from survryPrev::getDHSdata |
A partially processed data.frame that will be used in survryPrev::getDHSindicator. The whole function can be used as a parameter in survryPrev::getDHSindicator
Miaolei Bao, Yunhan Wu, Qianyu Dong
DV_PCPV_W_EMP
DV_PCPV_W_EMP(IRdata)DV_PCPV_W_EMP(IRdata)
IRdata |
data.frame from survryPrev::getDHSdata |
A partially processed data.frame that will be used in survryPrev::getDHSindicator. The whole function can be used as a parameter in survryPrev::getDHSindicator
Miaolei Bao, Yunhan Wu, Qianyu Dong
DV_PCPV_W_FLW
DV_PCPV_W_FLW(IRdata)DV_PCPV_W_FLW(IRdata)
IRdata |
data.frame from survryPrev::getDHSdata |
A partially processed data.frame that will be used in survryPrev::getDHSindicator. The whole function can be used as a parameter in survryPrev::getDHSindicator
Miaolei Bao, Yunhan Wu, Qianyu Dong
DV_PCPV_W_OLW
DV_PCPV_W_OLW(IRdata)DV_PCPV_W_OLW(IRdata)
IRdata |
data.frame from survryPrev::getDHSdata |
A partially processed data.frame that will be used in survryPrev::getDHSindicator. The whole function can be used as a parameter in survryPrev::getDHSindicator
Miaolei Bao, Yunhan Wu, Qianyu Dong
DV_STPS_W_BFR
DV_STPS_W_BFR(IRdata)DV_STPS_W_BFR(IRdata)
IRdata |
data.frame from survryPrev::getDHSdata |
A partially processed data.frame that will be used in survryPrev::getDHSindicator. The whole function can be used as a parameter in survryPrev::getDHSindicator
Miaolei Bao, Yunhan Wu, Qianyu Dong
DV_VPRG_W_VPG
DV_VPRG_W_VPG(IRdata)DV_VPRG_W_VPG(IRdata)
IRdata |
data.frame from survryPrev::getDHSdata |
A partially processed data.frame that will be used in survryPrev::getDHSindicator. The whole function can be used as a parameter in survryPrev::getDHSindicator
Miaolei Bao, Yunhan Wu, Qianyu Dong
ED_LITR_W_LIT
ED_LITR_W_LIT(IRdata)ED_LITR_W_LIT(IRdata)
IRdata |
data.frame from survryPrev::getDHSdata |
A partially processed data.frame that will be used in survryPrev::getDHSindicator. The whole function can be used as a parameter in survryPrev::getDHSindicator
Miaolei Bao, Yunhan Wu, Qianyu Dong
ED_MDIA_W_3MD
ED_MDIA_W_3MD(IRdata)ED_MDIA_W_3MD(IRdata)
IRdata |
data.frame from survryPrev::getDHSdata |
A partially processed data.frame that will be used in survryPrev::getDHSindicator. The whole function can be used as a parameter in survryPrev::getDHSindicator
Miaolei Bao, Yunhan Wu, Qianyu Dong
ED_MDIA_W_N3M
ED_MDIA_W_N3M(IRdata)ED_MDIA_W_N3M(IRdata)
IRdata |
data.frame from survryPrev::getDHSdata |
A partially processed data.frame that will be used in survryPrev::getDHSindicator. The whole function can be used as a parameter in survryPrev::getDHSindicator
Miaolei Bao, Yunhan Wu, Qianyu Dong
ED_MDIA_W_NWS
ED_MDIA_W_NWS(IRdata)ED_MDIA_W_NWS(IRdata)
IRdata |
data.frame from survryPrev::getDHSdata |
A partially processed data.frame that will be used in survryPrev::getDHSindicator. The whole function can be used as a parameter in survryPrev::getDHSindicator
Miaolei Bao, Yunhan Wu, Qianyu Dong
ED_MDIA_W_RDO
ED_MDIA_W_RDO(IRdata)ED_MDIA_W_RDO(IRdata)
IRdata |
data.frame from survryPrev::getDHSdata |
A partially processed data.frame that will be used in survryPrev::getDHSindicator. The whole function can be used as a parameter in survryPrev::getDHSindicator
Miaolei Bao, Yunhan Wu, Qianyu Dong
ED_MDIA_W_TLV
ED_MDIA_W_TLV(IRdata)ED_MDIA_W_TLV(IRdata)
IRdata |
data.frame from survryPrev::getDHSdata |
A partially processed data.frame that will be used in survryPrev::getDHSindicator. The whole function can be used as a parameter in survryPrev::getDHSindicator
Miaolei Bao, Yunhan Wu, Qianyu Dong
EM_EMPM_W_EMP
EM_EMPM_W_EMP(IRdata)EM_EMPM_W_EMP(IRdata)
IRdata |
data.frame from survryPrev::getDHSdata |
A partially processed data.frame that will be used in survryPrev::getDHSindicator. The whole function can be used as a parameter in survryPrev::getDHSindicator
Miaolei Bao, Yunhan Wu, Qianyu Dong
This function return a map of exceedance probability for given model results.
exceedPlot( x, exceed = TRUE, direction = 1, threshold = NA, geo = geo, by.geo = NULL, ylim = NULL, ... )exceedPlot( x, exceed = TRUE, direction = 1, threshold = NA, geo = geo, by.geo = NULL, ylim = NULL, ... )
x |
a model result using surveyPrev of class "fhModel" or "clusterModel" |
exceed |
direction of the comparison The default is exceed = TRUE, which correspond to probability of prevalence larger than the threshold. If exceed = FALSE, the plot computes probability smaller than the threshold. |
direction |
Direction of the color scheme. It can be either 1 (smaller values are darker) or -1 (higher values are darker). Default is set to 1. |
threshold |
the threshold to be used in computing the exceedance probability |
geo |
SpatialPolygonsDataFrame object for the map |
by.geo |
variable name specifying region names in the data |
ylim |
range of the values to be plotted. |
... |
additional arguments passed to SUMMER::mapPlot(). |
This function returns a map showing probability of prevalence over/under the threshold.
Zehang Li, Qianyu Dong
## Not run: geo <- getDHSgeo(country = "Zambia", year = 2018) data(ZambiaAdm1) data(ZambiaAdm2) data(ZambiaPopWomen) cluster.info <- clusterInfo(geo = geo, poly.adm1 = ZambiaAdm1, poly.adm2 = ZambiaAdm2) dhsData <- getDHSdata(country = "Zambia", indicator = "ancvisit4+", year = 2018) data <- getDHSindicator(dhsData, indicator = "ancvisit4+") admin.info2 <- adminInfo(poly.adm = ZambiaAdm2, admin = 2, by.adm="NAME_2", by.adm.upper = "NAME_1") cl_res_ad2_unstrat <- clusterModel(data = data, cluster.info = cluster.info, admin.info = admin.info2, stratification = FALSE, model = "bym2", admin = 2, aggregation = TRUE, CI = 0.95) ZambiaAdm2$admin2.name.full <- paste0(ZambiaAdm2$NAME_1, "_", ZambiaAdm2$NAME_2) exceedPlot(cl_res_ad2_unstrat, threshold = 0.5, exceed = TRUE, direction = -1, geo = ZambiaAdm2, by.geo = "admin2.name.full") exceedPlot(cl_res_ad2_unstrat, threshold = 0.5, exceed = FALSE, direction = -1, geo = ZambiaAdm2, by.geo = "admin2.name.full") ## End(Not run)## Not run: geo <- getDHSgeo(country = "Zambia", year = 2018) data(ZambiaAdm1) data(ZambiaAdm2) data(ZambiaPopWomen) cluster.info <- clusterInfo(geo = geo, poly.adm1 = ZambiaAdm1, poly.adm2 = ZambiaAdm2) dhsData <- getDHSdata(country = "Zambia", indicator = "ancvisit4+", year = 2018) data <- getDHSindicator(dhsData, indicator = "ancvisit4+") admin.info2 <- adminInfo(poly.adm = ZambiaAdm2, admin = 2, by.adm="NAME_2", by.adm.upper = "NAME_1") cl_res_ad2_unstrat <- clusterModel(data = data, cluster.info = cluster.info, admin.info = admin.info2, stratification = FALSE, model = "bym2", admin = 2, aggregation = TRUE, CI = 0.95) ZambiaAdm2$admin2.name.full <- paste0(ZambiaAdm2$NAME_1, "_", ZambiaAdm2$NAME_2) exceedPlot(cl_res_ad2_unstrat, threshold = 0.5, exceed = TRUE, direction = -1, geo = ZambiaAdm2, by.geo = "admin2.name.full") exceedPlot(cl_res_ad2_unstrat, threshold = 0.5, exceed = FALSE, direction = -1, geo = ZambiaAdm2, by.geo = "admin2.name.full") ## End(Not run)
This function calculate smoothed direct estimates at given admin level.
fhModel( data, cluster.info, admin.info = NULL, X = NULL, admin, CI = 0.95, model = c("bym2", "iid"), aggregation = FALSE, alt.strata = NULL, ... )fhModel( data, cluster.info, admin.info = NULL, X = NULL, admin, CI = 0.95, model = c("bym2", "iid"), aggregation = FALSE, alt.strata = NULL, ... )
data |
dataframe that contains the indicator of interests, output of getDHSindicator function |
cluster.info |
list contains data and wrong.points. data contains admin 1 and admin 2 information and coordinates for each cluster. wrong.points. contains cluster id for cluster without coordinates or admin 1 information. Output of getDHSindicator function |
admin.info |
list contains data and mat, data contains population and urban/rural proportion at specific admin level and mat is the adjacency matrix, output of adminInfo function |
X |
dataframe that contains areal covariates, the first column should be the same admin name as in admin.info$data. |
admin |
admin level for the model |
CI |
Credible interval to be used. Default to 0.95. |
model |
smoothing model used in the random effect. Options are independent ("iid") or spatial ("bym2"). |
aggregation |
whether or not report aggregation results. |
alt.strata |
the variable name in the data frame that correspond to the stratification variable. Most of the DHS surveys are stratified by admin 1 area crossed with urban/rural, which is the default stratification variable created by the function (when |
... |
Additional arguments passed on to the 'smoothSurvey' function |
This function returns the dataset that contain district name and population for given tiff files and polygons of admin level,
Qianyu Dong
## Not run: geo <- getDHSgeo(country = "Zambia", year = 2018) data(ZambiaAdm1) data(ZambiaAdm2) data(ZambiaPopWomen) cluster.info <- clusterInfo(geo = geo, poly.adm1 = ZambiaAdm1, poly.adm2 = ZambiaAdm2) dhsData <- getDHSdata(country = "Zambia", indicator = "ancvisit4+", year = 2018) data <- getDHSindicator(dhsData, indicator = "ancvisit4+") admin.info1 <- adminInfo(poly.adm = ZambiaAdm1, admin = 1, agg.pop =ZambiaPopWomen$admin1_pop, proportion = ZambiaPopWomen$admin1_urban) smth_res_ad1 <- fhModel(data, cluster.info = cluster.info, admin.info = admin.info1, admin = 1, model = "bym2", aggregation = F) smth_res_ad1 ## End(Not run)## Not run: geo <- getDHSgeo(country = "Zambia", year = 2018) data(ZambiaAdm1) data(ZambiaAdm2) data(ZambiaPopWomen) cluster.info <- clusterInfo(geo = geo, poly.adm1 = ZambiaAdm1, poly.adm2 = ZambiaAdm2) dhsData <- getDHSdata(country = "Zambia", indicator = "ancvisit4+", year = 2018) data <- getDHSindicator(dhsData, indicator = "ancvisit4+") admin.info1 <- adminInfo(poly.adm = ZambiaAdm1, admin = 1, agg.pop =ZambiaPopWomen$admin1_pop, proportion = ZambiaPopWomen$admin1_urban) smth_res_ad1 <- fhModel(data, cluster.info = cluster.info, admin.info = admin.info1, admin = 1, model = "bym2", aggregation = F) smth_res_ad1 ## End(Not run)
FP_CUSM_W_MOD IRdata Modern contraceptive prevalence rate (Married women currently using any modern method of contraception)
fp_cruse_mod(Rdata)fp_cruse_mod(Rdata)
Rdata |
data.frame from survryPrev::getDHSdata |
A partially processed data.frame that will be used in survryPrev::getDHSindicator. The whole function can be used as a parameter in survryPrev::getDHSindicator
Qianyu Dong
## Not run: dhsData <- getDHSdata(country = "Zambia", indicator = "FP_CUSA_W_MOD", year = 2018) data <- getDHSindicator(dhsData, indicator = NULL, FUN = surveyPrev::fp_cruse_mod) ## End(Not run)## Not run: dhsData <- getDHSdata(country = "Zambia", indicator = "FP_CUSA_W_MOD", year = 2018) data <- getDHSindicator(dhsData, indicator = NULL, FUN = surveyPrev::fp_cruse_mod) ## End(Not run)
FP_CUSA_W_ANY
FP_CUSA_W_ANY(IRdata)FP_CUSA_W_ANY(IRdata)
IRdata |
data.frame from survryPrev::getDHSdata |
A partially processed data.frame that will be used in survryPrev::getDHSindicator. The whole function can be used as a parameter in survryPrev::getDHSindicator
Miaolei Bao, Yunhan Wu, Qianyu Dong
FP_CUSA_W_EMC
FP_CUSA_W_EMC(IRdata)FP_CUSA_W_EMC(IRdata)
IRdata |
data.frame from survryPrev::getDHSdata |
A partially processed data.frame that will be used in survryPrev::getDHSindicator. The whole function can be used as a parameter in survryPrev::getDHSindicator
Miaolei Bao, Yunhan Wu, Qianyu Dong
FP_CUSA_W_FCN
FP_CUSA_W_FCN(IRdata)FP_CUSA_W_FCN(IRdata)
IRdata |
data.frame from survryPrev::getDHSdata |
A partially processed data.frame that will be used in survryPrev::getDHSindicator. The whole function can be used as a parameter in survryPrev::getDHSindicator
Miaolei Bao, Yunhan Wu, Qianyu Dong
FP_CUSA_W_FST
FP_CUSA_W_FST(IRdata)FP_CUSA_W_FST(IRdata)
IRdata |
data.frame from survryPrev::getDHSdata |
A partially processed data.frame that will be used in survryPrev::getDHSindicator. The whole function can be used as a parameter in survryPrev::getDHSindicator
Miaolei Bao, Yunhan Wu, Qianyu Dong
FP_CUSA_W_IMP
FP_CUSA_W_IMP(IRdata)FP_CUSA_W_IMP(IRdata)
IRdata |
data.frame from survryPrev::getDHSdata |
A partially processed data.frame that will be used in survryPrev::getDHSindicator. The whole function can be used as a parameter in survryPrev::getDHSindicator
Miaolei Bao, Yunhan Wu, Qianyu Dong
FP_CUSA_W_INJ
FP_CUSA_W_INJ(IRdata)FP_CUSA_W_INJ(IRdata)
IRdata |
data.frame from survryPrev::getDHSdata |
A partially processed data.frame that will be used in survryPrev::getDHSindicator. The whole function can be used as a parameter in survryPrev::getDHSindicator
Miaolei Bao, Yunhan Wu, Qianyu Dong
FP_CUSA_W_IUD
FP_CUSA_W_IUD(IRdata)FP_CUSA_W_IUD(IRdata)
IRdata |
data.frame from survryPrev::getDHSdata |
A partially processed data.frame that will be used in survryPrev::getDHSindicator. The whole function can be used as a parameter in survryPrev::getDHSindicator
Miaolei Bao, Yunhan Wu, Qianyu Dong
FP_CUSA_W_MCN
FP_CUSA_W_MCN(IRdata)FP_CUSA_W_MCN(IRdata)
IRdata |
data.frame from survryPrev::getDHSdata |
A partially processed data.frame that will be used in survryPrev::getDHSindicator. The whole function can be used as a parameter in survryPrev::getDHSindicator
Miaolei Bao, Yunhan Wu, Qianyu Dong
FP_CUSA_W_MST
FP_CUSA_W_MST(IRdata)FP_CUSA_W_MST(IRdata)
IRdata |
data.frame from survryPrev::getDHSdata |
A partially processed data.frame that will be used in survryPrev::getDHSindicator. The whole function can be used as a parameter in survryPrev::getDHSindicator
Miaolei Bao, Yunhan Wu, Qianyu Dong
FP_CUSA_W_PIL
FP_CUSA_W_PIL(IRdata)FP_CUSA_W_PIL(IRdata)
IRdata |
data.frame from survryPrev::getDHSdata |
A partially processed data.frame that will be used in survryPrev::getDHSindicator. The whole function can be used as a parameter in survryPrev::getDHSindicator
Miaolei Bao, Yunhan Wu, Qianyu Dong
FP_CUSA_W_STD
FP_CUSA_W_STD(IRdata)FP_CUSA_W_STD(IRdata)
IRdata |
data.frame from survryPrev::getDHSdata |
A partially processed data.frame that will be used in survryPrev::getDHSindicator. The whole function can be used as a parameter in survryPrev::getDHSindicator
Miaolei Bao, Yunhan Wu, Qianyu Dong
FP_CUSA_W_TRA
FP_CUSA_W_TRA(IRdata)FP_CUSA_W_TRA(IRdata)
IRdata |
data.frame from survryPrev::getDHSdata |
A partially processed data.frame that will be used in survryPrev::getDHSindicator. The whole function can be used as a parameter in survryPrev::getDHSindicator
Miaolei Bao, Yunhan Wu, Qianyu Dong
FP_CUSA_W_WTH
FP_CUSA_W_WTH(IRdata)FP_CUSA_W_WTH(IRdata)
IRdata |
data.frame from survryPrev::getDHSdata |
A partially processed data.frame that will be used in survryPrev::getDHSindicator. The whole function can be used as a parameter in survryPrev::getDHSindicator
Miaolei Bao, Yunhan Wu, Qianyu Dong
FP_EFPM_M_NWS
FP_EFPM_M_NWS(MRdata)FP_EFPM_M_NWS(MRdata)
MRdata |
data.frame from survryPrev::getDHSdata |
A partially processed data.frame that will be used in survryPrev::getDHSindicator. The whole function can be used as a parameter in survryPrev::getDHSindicator
Miaolei Bao, Yunhan Wu, Qianyu Dong
FP_EFPM_M_TLV
FP_EFPM_M_TLV(MRdata)FP_EFPM_M_TLV(MRdata)
MRdata |
data.frame from survryPrev::getDHSdata |
A partially processed data.frame that will be used in survryPrev::getDHSindicator. The whole function can be used as a parameter in survryPrev::getDHSindicator
Miaolei Bao, Yunhan Wu, Qianyu Dong
FP_EFPM_W_NWS
FP_EFPM_W_NWS(IRdata)FP_EFPM_W_NWS(IRdata)
IRdata |
data.frame from survryPrev::getDHSdata |
A partially processed data.frame that will be used in survryPrev::getDHSindicator. The whole function can be used as a parameter in survryPrev::getDHSindicator
Miaolei Bao, Yunhan Wu, Qianyu Dong
FP_EFPM_W_RDO
FP_EFPM_W_RDO(IRdata)FP_EFPM_W_RDO(IRdata)
IRdata |
data.frame from survryPrev::getDHSdata |
A partially processed data.frame that will be used in survryPrev::getDHSindicator. The whole function can be used as a parameter in survryPrev::getDHSindicator
Miaolei Bao, Yunhan Wu, Qianyu Dong
FP_EFPM_W_TLV
FP_EFPM_W_TLV(IRdata)FP_EFPM_W_TLV(IRdata)
IRdata |
data.frame from survryPrev::getDHSdata |
A partially processed data.frame that will be used in survryPrev::getDHSindicator. The whole function can be used as a parameter in survryPrev::getDHSindicator
Miaolei Bao, Yunhan Wu, Qianyu Dong
FP_EVUM_W_MOD
FP_EVUM_W_MOD(Rdata)FP_EVUM_W_MOD(Rdata)
Rdata |
data.frame from survryPrev::getDHSdata |
A partially processed data.frame that will be used in survryPrev::getDHSindicator. The whole function can be used as a parameter in survryPrev::getDHSindicator
Miaolei Bao, Yunhan Wu, Qianyu Dong
FP_KMTA_W_ANY
FP_KMTA_W_ANY(IRdata)FP_KMTA_W_ANY(IRdata)
IRdata |
data.frame from survryPrev::getDHSdata |
A partially processed data.frame that will be used in survryPrev::getDHSindicator. The whole function can be used as a parameter in survryPrev::getDHSindicator
Miaolei Bao, Yunhan Wu, Qianyu Dong
FP_KMTA_W_EMC
FP_KMTA_W_EMC(IRdata)FP_KMTA_W_EMC(IRdata)
IRdata |
data.frame from survryPrev::getDHSdata |
A partially processed data.frame that will be used in survryPrev::getDHSindicator. The whole function can be used as a parameter in survryPrev::getDHSindicator
Miaolei Bao, Yunhan Wu, Qianyu Dong
FP_KMTA_W_FCN
FP_KMTA_W_FCN(IRdata)FP_KMTA_W_FCN(IRdata)
IRdata |
data.frame from survryPrev::getDHSdata |
A partially processed data.frame that will be used in survryPrev::getDHSindicator. The whole function can be used as a parameter in survryPrev::getDHSindicator
Miaolei Bao, Yunhan Wu, Qianyu Dong
FP_KMTA_W_FST
FP_KMTA_W_FST(IRdata)FP_KMTA_W_FST(IRdata)
IRdata |
data.frame from survryPrev::getDHSdata |
A partially processed data.frame that will be used in survryPrev::getDHSindicator. The whole function can be used as a parameter in survryPrev::getDHSindicator
Miaolei Bao, Yunhan Wu, Qianyu Dong
FP_KMTA_W_IMP
FP_KMTA_W_IMP(IRdata)FP_KMTA_W_IMP(IRdata)
IRdata |
data.frame from survryPrev::getDHSdata |
A partially processed data.frame that will be used in survryPrev::getDHSindicator. The whole function can be used as a parameter in survryPrev::getDHSindicator
Miaolei Bao, Yunhan Wu, Qianyu Dong
FP_KMTA_W_INJ
FP_KMTA_W_INJ(IRdata)FP_KMTA_W_INJ(IRdata)
IRdata |
data.frame from survryPrev::getDHSdata |
A partially processed data.frame that will be used in survryPrev::getDHSindicator. The whole function can be used as a parameter in survryPrev::getDHSindicator
Miaolei Bao, Yunhan Wu, Qianyu Dong
FP_KMTA_W_IUD
FP_KMTA_W_IUD(IRdata)FP_KMTA_W_IUD(IRdata)
IRdata |
data.frame from survryPrev::getDHSdata |
A partially processed data.frame that will be used in survryPrev::getDHSindicator. The whole function can be used as a parameter in survryPrev::getDHSindicator
Miaolei Bao, Yunhan Wu, Qianyu Dong
FP_KMTA_W_MST
FP_KMTA_W_MST(IRdata)FP_KMTA_W_MST(IRdata)
IRdata |
data.frame from survryPrev::getDHSdata |
A partially processed data.frame that will be used in survryPrev::getDHSindicator. The whole function can be used as a parameter in survryPrev::getDHSindicator
Miaolei Bao, Yunhan Wu, Qianyu Dong
FP_KMTA_W_OMD
FP_KMTA_W_OMD(IRdata)FP_KMTA_W_OMD(IRdata)
IRdata |
data.frame from survryPrev::getDHSdata |
A partially processed data.frame that will be used in survryPrev::getDHSindicator. The whole function can be used as a parameter in survryPrev::getDHSindicator
Miaolei Bao, Yunhan Wu, Qianyu Dong
FP_KMTA_W_PIL
FP_KMTA_W_PIL(IRdata)FP_KMTA_W_PIL(IRdata)
IRdata |
data.frame from survryPrev::getDHSdata |
A partially processed data.frame that will be used in survryPrev::getDHSindicator. The whole function can be used as a parameter in survryPrev::getDHSindicator
Miaolei Bao, Yunhan Wu, Qianyu Dong
FP_KMTA_W_STD
FP_KMTA_W_STD(IRdata)FP_KMTA_W_STD(IRdata)
IRdata |
data.frame from survryPrev::getDHSdata |
A partially processed data.frame that will be used in survryPrev::getDHSindicator. The whole function can be used as a parameter in survryPrev::getDHSindicator
Miaolei Bao, Yunhan Wu, Qianyu Dong
FP_KMTA_W_TRA
FP_KMTA_W_TRA(IRdata)FP_KMTA_W_TRA(IRdata)
IRdata |
data.frame from survryPrev::getDHSdata |
A partially processed data.frame that will be used in survryPrev::getDHSindicator. The whole function can be used as a parameter in survryPrev::getDHSindicator
Miaolei Bao, Yunhan Wu, Qianyu Dong
FP_KMTA_W_WTH
FP_KMTA_W_WTH(IRdata)FP_KMTA_W_WTH(IRdata)
IRdata |
data.frame from survryPrev::getDHSdata |
A partially processed data.frame that will be used in survryPrev::getDHSindicator. The whole function can be used as a parameter in survryPrev::getDHSindicator
Miaolei Bao, Yunhan Wu, Qianyu Dong
FP_NADA_W_UNT #unmet_family IRdata women with an unmet need for family planning for spacing and limiting
fp_unmet_tot(Rdata)fp_unmet_tot(Rdata)
Rdata |
data.frame from survryPrev::getDHSdata |
A partially processed data.frame that will be used in survryPrev::getDHSindicator. The whole function can be used as a parameter in survryPrev::getDHSindicator
Qianyu Dong
## Not run: dhsData <- getDHSdata(country = "Zambia", indicator = "FP_NADA_W_UNT", year = 2018) data <- getDHSindicator(dhsData, indicator = NULL, FUN = surveyPrev::fp_unmet_tot) ## End(Not run)## Not run: dhsData <- getDHSdata(country = "Zambia", indicator = "FP_NADA_W_UNT", year = 2018) data <- getDHSindicator(dhsData, indicator = NULL, FUN = surveyPrev::fp_unmet_tot) ## End(Not run)
Function to obtain subnational estimates from DHS API
get_api_table(country, survey, indicator, simplify = TRUE, admin = 1)get_api_table(country, survey, indicator, simplify = TRUE, admin = 1)
country |
A character string of keys at: https://api.dhsprogram.com/rest/dhs/countries?returnFields=CountryName,DHS_CountryCode&f=html |
survey |
A character string of keys at: https://api.dhsprogram.com/rest/dhs/surveys?returnFields=SurveyId,SurveyYearLabel,SurveyType,CountryName&f=html |
indicator |
A character string of keys at: https://api.dhsprogram.com/rest/dhs/indicators?returnFields=IndicatorId,Label,Definition&f=html |
simplify |
if TRUE only the value and region index is returned. |
admin |
Either 0 (national) or 1 (subnational admin 1 area). |
a data frame of the DHS indicator estimates
## Not run: # country: Zambia # survey: 2018 DHS # indicator: Percentage of children stunted # (below -2 SD of height for age # according to the WHO standard) dhs_table <- get_api_table(country = "ZM", survey = "ZM2018DHS", indicator = "CN_NUTS_C_HA2", simplify = TRUE) dhs_table ## End(Not run)## Not run: # country: Zambia # survey: 2018 DHS # indicator: Percentage of children stunted # (below -2 SD of height for age # according to the WHO standard) dhs_table <- get_api_table(country = "ZM", survey = "ZM2018DHS", indicator = "CN_NUTS_C_HA2", simplify = TRUE) dhs_table ## End(Not run)
This function downloads DHS data for a particular country and survey.
getDHSdata(country, indicator = NULL, Recode = NULL, year)getDHSdata(country, indicator = NULL, Recode = NULL, year)
country |
Country name. |
indicator |
Indicator of interests. Current list of supported indicators include: "womananemia", "ancvisit4+", "stunting", "wasting", "DPT3". |
Recode |
Types of dhs Recode |
year |
Year the survey conducted. |
This function returns the survey dataset that contains the indicator.
Qianyu Dong
## Not run: # When indicator is known, download only the relevant file dhsData <- getDHSdata(country = "Zambia", indicator = "ancvisit4+", year = 2018) # When indicator is NULL or not recognized, download all files dhsData <- getDHSdata(country = "Zambia", indicator = NULL, year = 2018) names(dhsData) ## End(Not run)## Not run: # When indicator is known, download only the relevant file dhsData <- getDHSdata(country = "Zambia", indicator = "ancvisit4+", year = 2018) # When indicator is NULL or not recognized, download all files dhsData <- getDHSdata(country = "Zambia", indicator = NULL, year = 2018) names(dhsData) ## End(Not run)
This function downloads cluster's coordinate data for country and survey.
getDHSgeo(country, year)getDHSgeo(country, year)
country |
Country name. |
year |
Year the survey conducted. |
The function returns a spatial point dataset with coordinates for each cluster based on the chosen survey and year.
Qianyu Dong
## Not run: geo <- getDHSgeo(country = "Zambia", year = 2018) ## End(Not run)## Not run: geo <- getDHSgeo(country = "Zambia", year = 2018) ## End(Not run)
This function processes DHS data from getDHSdata function.
getDHSindicator( Rdata, indicator = NULL, FUN = NULL, nmr.year = 10, filter = NULL, yesCondition = NULL, noCondition = NULL )getDHSindicator( Rdata, indicator = NULL, FUN = NULL, nmr.year = 10, filter = NULL, yesCondition = NULL, noCondition = NULL )
Rdata |
Result from getDHSdata function, the raw DHS survry data from get_datasets. |
indicator |
Indicator of interests. |
FUN |
a function to process the DHS data into a binary indicator if not using one of the implemented indicators. See surveyPrev::AN_ANEM_W_ANY for an example function to obtain the indicator for women classified as having any anemia. |
nmr.year |
This is an argument specifically for NMR calculation. It specifies births how many years do we include prior to the date of survey. Default to be 10, i.e., NMR in the last 10 years prior to survey. |
filter |
This arguments specifies how the data should be filtered for creating a customized indicator. It should be a character string or a vector of character strings specifying the expression used to filter the data. See example for details |
yesCondition |
This arguments specifies how to define a yes label, i.e., value = 1, for creating a customized indicator. It should be a character string specifying the expression used to define the outcome value equal to 1. See example for details. |
noCondition |
This arguments specifies how to define a no label, i.e., value = 0, for creating a customized indicator. It should be a character string specifying the expression used to define the outcome value equal to 0. See example for details. |
The function returns processed survey data that contains the indicator of interests.
Qianyu Dong
## Not run: dhsData1 <- getDHSdata(country = "Zambia", indicator = "ancvisit4+", year = 2018) data1 <- getDHSindicator(dhsData1, indicator = "ancvisit4+") #------------------------------------------------------------------# # User-specified function to process the data # For example see the internal function surveyPrev::AN_ANEM_W_ANY #------------------------------------------------------------------# dhsData2 <- getDHSdata(country = "Zambia", indicator = NULL, year = 2018) data2 <- getDHSindicator(dhsData2, indicator = NULL, FUN = surveyPrev::AN_ANEM_W_ANY) # which should be identical to the following dhsData3 <- getDHSdata(country = "Zambia", indicator = "womananemia", year = 2018) data3 <- getDHSindicator(dhsData3, indicator = "womananemia") #------------------------------------------------------------------# # User-specified filtering condition # Demonstrating NMR data preparation by specifying how to subset data # and specify the outcome variable and its levels #------------------------------------------------------------------# Recode <- "Births Recode" dhsData4 <- getDHSdata(country = "Zambia", indicator = NULL, Recode=Recode,year = "2018") # # Here we filter the births to be within the last 10 years # this is specified by condition = "v008 - b3 < 120" # b3 is the date of births in CMC format # v008 is the date of interview in CMC format # the difference is the number of months between the two dates # b7 is the age of death for the child. We consider neonatal deaths where # b7 = 0. # b7 = NA when the child is alive at the time of interview. data4 <- getDHSindicator(Rdata = dhsData4, indicator = NULL, filter = "v008 - b3 < 120", yesCondition = "b7 == 0", noCondition = "b7 > 0 | is.na(b7)") # This will return the same dataset as below data5 <- getDHSindicator(Rdata = dhsData4, indicator = "nmr") # Notice that filter can have more than one conditions specified by vector # The following four specifications lead to the same dataset for # neonatal deaths in the last 5 years data6a <- getDHSindicator(Rdata = dhsData4, indicator = NULL, filter = "v008 - b3 < 120 & v008 - b3 < 60", yesCondition = "b7 == 0", noCondition = "b7 > 0 | is.na(b7)") data6b <- getDHSindicator(Rdata = dhsData4, indicator = NULL, filter = c("v008 - b3 < 120", "v008 - b3 < 60"), yesCondition = "b7 == 0", noCondition = "b7 > 0 | is.na(b7)") data6c <- getDHSindicator(Rdata = dhsData4, indicator = NULL, filter = "v008 - b3 < 60", yesCondition = "b7 == 0", noCondition = "b7 > 0 | is.na(b7)") data7 <- getDHSindicator(Rdata = dhsData4, indicator = "nmr", nmr.year = 5) ## End(Not run)## Not run: dhsData1 <- getDHSdata(country = "Zambia", indicator = "ancvisit4+", year = 2018) data1 <- getDHSindicator(dhsData1, indicator = "ancvisit4+") #------------------------------------------------------------------# # User-specified function to process the data # For example see the internal function surveyPrev::AN_ANEM_W_ANY #------------------------------------------------------------------# dhsData2 <- getDHSdata(country = "Zambia", indicator = NULL, year = 2018) data2 <- getDHSindicator(dhsData2, indicator = NULL, FUN = surveyPrev::AN_ANEM_W_ANY) # which should be identical to the following dhsData3 <- getDHSdata(country = "Zambia", indicator = "womananemia", year = 2018) data3 <- getDHSindicator(dhsData3, indicator = "womananemia") #------------------------------------------------------------------# # User-specified filtering condition # Demonstrating NMR data preparation by specifying how to subset data # and specify the outcome variable and its levels #------------------------------------------------------------------# Recode <- "Births Recode" dhsData4 <- getDHSdata(country = "Zambia", indicator = NULL, Recode=Recode,year = "2018") # # Here we filter the births to be within the last 10 years # this is specified by condition = "v008 - b3 < 120" # b3 is the date of births in CMC format # v008 is the date of interview in CMC format # the difference is the number of months between the two dates # b7 is the age of death for the child. We consider neonatal deaths where # b7 = 0. # b7 = NA when the child is alive at the time of interview. data4 <- getDHSindicator(Rdata = dhsData4, indicator = NULL, filter = "v008 - b3 < 120", yesCondition = "b7 == 0", noCondition = "b7 > 0 | is.na(b7)") # This will return the same dataset as below data5 <- getDHSindicator(Rdata = dhsData4, indicator = "nmr") # Notice that filter can have more than one conditions specified by vector # The following four specifications lead to the same dataset for # neonatal deaths in the last 5 years data6a <- getDHSindicator(Rdata = dhsData4, indicator = NULL, filter = "v008 - b3 < 120 & v008 - b3 < 60", yesCondition = "b7 == 0", noCondition = "b7 > 0 | is.na(b7)") data6b <- getDHSindicator(Rdata = dhsData4, indicator = NULL, filter = c("v008 - b3 < 120", "v008 - b3 < 60"), yesCondition = "b7 == 0", noCondition = "b7 > 0 | is.na(b7)") data6c <- getDHSindicator(Rdata = dhsData4, indicator = NULL, filter = "v008 - b3 < 60", yesCondition = "b7 == 0", noCondition = "b7 > 0 | is.na(b7)") data7 <- getDHSindicator(Rdata = dhsData4, indicator = "nmr", nmr.year = 5) ## End(Not run)
This function computes the urban proportion at a given survey year. It requires two population raster files and urban population fraction by admin 1 area from the census. The census year overall population raster is used to partition the grids into urban and rural pixels, based on the urban population fractions in a given area at the census year. The thresholding process is performed by first sorting the pixels from high to low population density, and find a threshold such that the fraction of population above this threshold matches the urban population fraction from the census. This step defines the urbanicity of each pixel. In the second step, for any given year's raster for a specific (sub-)population (e.g., specific age groups), we aggregate the population in the urban pixels defined in the previous step to compute urban proportion for the (sub-)population, within both admin1 and admin2 regions.
getUR( tiff.census, tiff.survey, prop.census, fact = 10, poly.adm1, poly.adm2, varname1, varname2 )getUR( tiff.census, tiff.survey, prop.census, fact = 10, poly.adm1, poly.adm2, varname1, varname2 )
tiff.census |
spatial raster of population estimates at the census year when the sampling frame is based, for the whole population. |
tiff.survey |
spatial raster of population estimates at the survey year, for the target population. |
prop.census |
a data frame with two columns: 'admin1' column correspond to the admin 1 names in the 'poly.adm1' file. And 'frac' column specifying the proportion of population in each admin 1 area during the census year. See examples for detail. |
fact |
factor to aggregate pixels from tiff.survey to tiff.census. For example, if tiff.census is a population raster at 1km by 1km resolution and tiff.survey is a raster at 100m by 100m resolution, then fact should be set to 10. Currently we only support fact > 1. Default is 10. |
poly.adm1 |
spatial polygons data frame for admin 1 |
poly.adm2 |
spatial polygons data frame for admin 2 |
varname1 |
column name of district name in the admin 1 spatial polygon data frame |
varname2 |
column name of district name in the admin 2 spatial polygon data frame |
a list of two data frames for admin 1 and admin 2 urban ratios
## Not run: # ----------------------------------------------------------------------# # Here we consider the example of computing urban/rural fraction for # Zambia 2018 DHS for the sub-population of children under 1 years old. # This survey is based on sampling frame from the 2010 Zambia Census. # ----------------------------------------------------------------------# # # From Table A1 of Zambia 2013-2014 DHS final report, we can obtain the fraction of # urban population by Admin 1 areas in the 2010 survey. # Notice that in the appendix of the 2018 DHS final report, # only distribution of household is reported and not population size by urbanicity. # When the table is not provided in the DHS report, you need to find it from # the census website directly. # Please note that the admin1 column needs to match the admin 1 names in the # Admin 1 spatial polygon file exactly. # For example, here we change "Northwestern" to "North-Western" urban.frac <- data.frame( admin1 = c('Central', 'Copperbelt', 'Eastern', 'Luapula', 'Lusaka', 'Muchinga', 'North-Western', 'Northern', 'Southern','Western'), frac = c(0.2513, 0.809, 0.1252, 0.1963, 0.8456, 0.1714, 0.2172, 0.1826, 0.2448, 0.1474)) # The corresponding census year population tiff can be found at: # https://data.worldpop.org/GIS/Population/Global_2000_2020_1km_UNadj/ # The code below downloads the file from the internet directly # You can also download the file directly and read into R link1="https://data.worldpop.org/GIS/Population/Global_2000_2020_1km_UNadj/" file1="2010/ZMB/zmb_ppp_2010_1km_Aggregated_UNadj.tif" tempfile1 = tempfile() download.file(paste0(link1, file1), destfile = tempfile1, method = "libcurl", mode="wb") library(raster) tiff1 <- raster(tempfile1) # https://hub.worldpop.org/geodata/summary?id=16429 # Here we compute population fractions for 0-1 year old population. # The from the same link below link2="https://data.worldpop.org/GIS/AgeSex_structures/Global_2000_2020/" # The two files are for female and male population respectively, file2f="2018/ZMB/zmb_f_0_2018.tif" file2m="2018/ZMB/zmb_f_0_2018.tif" # Since the two files are very large, we recommend downloading them # mannually and then load them into R. tiff2f <- raster("zmb_f_0_2018.tif") tiff2m <- raster("zmb_m_0_2018.tif") tiff2 <- tiff2f + tiff2m frac <- getUR(tiff.census = tiff1, tiff.survey = tiff2, prop.census = urban.frac, fact = 10, poly.adm1 = ZambiaAdm1, poly.adm2 = ZambiaAdm2, varname1 = "NAME_1", varname2 = "NAME_2") library(SUMMER) mapPlot(frac$admin1.ur, geo = ZambiaAdm1, by.data = "admin1.name", by.geo = "NAME_1", variable = "urban") mapPlot(frac$admin2.ur, geo = ZambiaAdm2, by.data = "admin2.name", by.geo = "NAME_2", variable = "urban") # Compare with the proportion of Women 14-49 years old in the built-in data # These two plots should be similar but not identical # since the population is different mapPlot(ZambiaPopWomen$admin2_urban, geo = ZambiaAdm2, by.data = "admin2.name", by.geo = "NAME_2", variable = "urban") ## End(Not run)## Not run: # ----------------------------------------------------------------------# # Here we consider the example of computing urban/rural fraction for # Zambia 2018 DHS for the sub-population of children under 1 years old. # This survey is based on sampling frame from the 2010 Zambia Census. # ----------------------------------------------------------------------# # # From Table A1 of Zambia 2013-2014 DHS final report, we can obtain the fraction of # urban population by Admin 1 areas in the 2010 survey. # Notice that in the appendix of the 2018 DHS final report, # only distribution of household is reported and not population size by urbanicity. # When the table is not provided in the DHS report, you need to find it from # the census website directly. # Please note that the admin1 column needs to match the admin 1 names in the # Admin 1 spatial polygon file exactly. # For example, here we change "Northwestern" to "North-Western" urban.frac <- data.frame( admin1 = c('Central', 'Copperbelt', 'Eastern', 'Luapula', 'Lusaka', 'Muchinga', 'North-Western', 'Northern', 'Southern','Western'), frac = c(0.2513, 0.809, 0.1252, 0.1963, 0.8456, 0.1714, 0.2172, 0.1826, 0.2448, 0.1474)) # The corresponding census year population tiff can be found at: # https://data.worldpop.org/GIS/Population/Global_2000_2020_1km_UNadj/ # The code below downloads the file from the internet directly # You can also download the file directly and read into R link1="https://data.worldpop.org/GIS/Population/Global_2000_2020_1km_UNadj/" file1="2010/ZMB/zmb_ppp_2010_1km_Aggregated_UNadj.tif" tempfile1 = tempfile() download.file(paste0(link1, file1), destfile = tempfile1, method = "libcurl", mode="wb") library(raster) tiff1 <- raster(tempfile1) # https://hub.worldpop.org/geodata/summary?id=16429 # Here we compute population fractions for 0-1 year old population. # The from the same link below link2="https://data.worldpop.org/GIS/AgeSex_structures/Global_2000_2020/" # The two files are for female and male population respectively, file2f="2018/ZMB/zmb_f_0_2018.tif" file2m="2018/ZMB/zmb_f_0_2018.tif" # Since the two files are very large, we recommend downloading them # mannually and then load them into R. tiff2f <- raster("zmb_f_0_2018.tif") tiff2m <- raster("zmb_m_0_2018.tif") tiff2 <- tiff2f + tiff2m frac <- getUR(tiff.census = tiff1, tiff.survey = tiff2, prop.census = urban.frac, fact = 10, poly.adm1 = ZambiaAdm1, poly.adm2 = ZambiaAdm2, varname1 = "NAME_1", varname2 = "NAME_2") library(SUMMER) mapPlot(frac$admin1.ur, geo = ZambiaAdm1, by.data = "admin1.name", by.geo = "NAME_1", variable = "urban") mapPlot(frac$admin2.ur, geo = ZambiaAdm2, by.data = "admin2.name", by.geo = "NAME_2", variable = "urban") # Compare with the proportion of Women 14-49 years old in the built-in data # These two plots should be similar but not identical # since the population is different mapPlot(ZambiaPopWomen$admin2_urban, geo = ZambiaAdm2, by.data = "admin2.name", by.geo = "NAME_2", variable = "urban") ## End(Not run)
HA_AFSY_M_A15
HA_AFSY_M_A15(MRdata)HA_AFSY_M_A15(MRdata)
MRdata |
data.frame from survryPrev::getDHSdata |
A partially processed data.frame that will be used in survryPrev::getDHSindicator. The whole function can be used as a parameter in survryPrev::getDHSindicator
Miaolei Bao, Yunhan Wu, Qianyu Dong
HA_AFSY_M_A18
HA_AFSY_M_A18(MRdata)HA_AFSY_M_A18(MRdata)
MRdata |
data.frame from survryPrev::getDHSdata |
A partially processed data.frame that will be used in survryPrev::getDHSindicator. The whole function can be used as a parameter in survryPrev::getDHSindicator
Miaolei Bao, Yunhan Wu, Qianyu Dong
HA_AFSY_W_A18
HA_AFSY_W_A18(IRdata)HA_AFSY_W_A18(IRdata)
IRdata |
data.frame from survryPrev::getDHSdata |
A partially processed data.frame that will be used in survryPrev::getDHSindicator. The whole function can be used as a parameter in survryPrev::getDHSindicator
Miaolei Bao, Yunhan Wu, Qianyu Dong
HA_ANSS_M_CND
HA_ANSS_M_CND(MRdata)HA_ANSS_M_CND(MRdata)
MRdata |
data.frame from survryPrev::getDHSdata |
A partially processed data.frame that will be used in survryPrev::getDHSindicator. The whole function can be used as a parameter in survryPrev::getDHSindicator
Miaolei Bao, Yunhan Wu, Qianyu Dong
HA_ANSS_W_CND
HA_ANSS_W_CND(IRdata)HA_ANSS_W_CND(IRdata)
IRdata |
data.frame from survryPrev::getDHSdata |
A partially processed data.frame that will be used in survryPrev::getDHSindicator. The whole function can be used as a parameter in survryPrev::getDHSindicator
Miaolei Bao, Yunhan Wu, Qianyu Dong
HA_ANSS_W_RSX
HA_ANSS_W_RSX(IRdata)HA_ANSS_W_RSX(IRdata)
IRdata |
data.frame from survryPrev::getDHSdata |
A partially processed data.frame that will be used in survryPrev::getDHSindicator. The whole function can be used as a parameter in survryPrev::getDHSindicator
Miaolei Bao, Yunhan Wu, Qianyu Dong
HA_CATH_W_ATN
HA_CATH_W_ATN(IRdata)HA_CATH_W_ATN(IRdata)
IRdata |
data.frame from survryPrev::getDHSdata |
A partially processed data.frame that will be used in survryPrev::getDHSindicator. The whole function can be used as a parameter in survryPrev::getDHSindicator
A partially processed data.frame that will be used in survryPrev::getDHSindicator. The whole function can be used as a parameter in survryPrev::getDHSindicator
A partially processed data.frame that will be used in survryPrev::getDHSindicator. The whole function can be used as a parameter in survryPrev::getDHSindicator
Miaolei Bao, Yunhan Wu, Qianyu Dong
HA_CATH_W_NRS
HA_CATH_W_NRS(IRdata)HA_CATH_W_NRS(IRdata)
IRdata |
data.frame from survryPrev::getDHSdata |
A partially processed data.frame that will be used in survryPrev::getDHSindicator. The whole function can be used as a parameter in survryPrev::getDHSindicator
A partially processed data.frame that will be used in survryPrev::getDHSindicator. The whole function can be used as a parameter in survryPrev::getDHSindicator
A partially processed data.frame that will be used in survryPrev::getDHSindicator. The whole function can be used as a parameter in survryPrev::getDHSindicator
Miaolei Bao, Yunhan Wu, Qianyu Dong
HA_HRSX_W_CND
HA_HRSX_W_CND(IRdata)HA_HRSX_W_CND(IRdata)
IRdata |
data.frame from survryPrev::getDHSdata |
A partially processed data.frame that will be used in survryPrev::getDHSindicator. The whole function can be used as a parameter in survryPrev::getDHSindicator
Miaolei Bao, Yunhan Wu, Qianyu Dong
HA_HVST_M_HRD
HA_HVST_M_HRD(MRdata)HA_HVST_M_HRD(MRdata)
MRdata |
data.frame from survryPrev::getDHSdata |
A partially processed data.frame that will be used in survryPrev::getDHSindicator. The whole function can be used as a parameter in survryPrev::getDHSindicator
Miaolei Bao, Yunhan Wu, Qianyu Dong
HA_HVST_M_USD
HA_HVST_M_USD(MRdata)HA_HVST_M_USD(MRdata)
MRdata |
data.frame from survryPrev::getDHSdata |
A partially processed data.frame that will be used in survryPrev::getDHSindicator. The whole function can be used as a parameter in survryPrev::getDHSindicator
Miaolei Bao, Yunhan Wu, Qianyu Dong
HA_HVTY_M_TRR
HA_HVTY_M_TRR(MRdata)HA_HVTY_M_TRR(MRdata)
MRdata |
data.frame from survryPrev::getDHSdata |
A partially processed data.frame that will be used in survryPrev::getDHSindicator. The whole function can be used as a parameter in survryPrev::getDHSindicator
Miaolei Bao, Yunhan Wu, Qianyu Dong
HA_HVTY_W_TRR
HA_HVTY_W_TRR(IRdata)HA_HVTY_W_TRR(IRdata)
IRdata |
data.frame from survryPrev::getDHSdata |
A partially processed data.frame that will be used in survryPrev::getDHSindicator. The whole function can be used as a parameter in survryPrev::getDHSindicator
Miaolei Bao, Yunhan Wu, Qianyu Dong
HA_KAID_W_HRD Percentage of women who have heard of HIV or AIDS hk_ever_heard in github IR
HA_KAID_W_HRD(Rdata)HA_KAID_W_HRD(Rdata)
Rdata |
data.frame from survryPrev::getDHSdata |
A partially processed data.frame that will be used in survryPrev::getDHSindicator. The whole function can be used as a parameter in survryPrev::getDHSindicator
Miaolei Bao, Yunhan Wu, Qianyu Dong
HA_STIS_M_DIS
HA_STIS_M_DIS(MRdata)HA_STIS_M_DIS(MRdata)
MRdata |
data.frame from survryPrev::getDHSdata |
A partially processed data.frame that will be used in survryPrev::getDHSindicator. The whole function can be used as a parameter in survryPrev::getDHSindicator
Miaolei Bao, Yunhan Wu, Qianyu Dong
HA_STIS_M_SOR
HA_STIS_M_SOR(MRdata)HA_STIS_M_SOR(MRdata)
MRdata |
data.frame from survryPrev::getDHSdata |
A partially processed data.frame that will be used in survryPrev::getDHSindicator. The whole function can be used as a parameter in survryPrev::getDHSindicator
Miaolei Bao, Yunhan Wu, Qianyu Dong
HA_STIS_W_STI Percentage of women reporting a sexually transmitted infection in the 12 months preceding the survey among women who ever had sexual intercourse hk_sti in github IR
HA_STIS_W_STI(Rdata)HA_STIS_W_STI(Rdata)
Rdata |
data.frame from survryPrev::getDHSdata |
A partially processed data.frame that will be used in survryPrev::getDHSindicator. The whole function can be used as a parameter in survryPrev::getDHSindicator
Miaolei Bao, Yunhan Wu, Qianyu Dong
HC_AGEG_P_ADL
HC_AGEG_P_ADL(PRdata)HC_AGEG_P_ADL(PRdata)
PRdata |
data.frame from survryPrev::getDHSdata |
A partially processed data.frame that will be used in survryPrev::getDHSindicator. The whole function can be used as a parameter in survryPrev::getDHSindicator
Miaolei Bao, Yunhan Wu, Qianyu Dong
HC_ELEC_H_ELC Percentage of households with electricity ph_electric in github HR
HC_ELEC_H_ELC(Rdata)HC_ELEC_H_ELC(Rdata)
Rdata |
data.frame from survryPrev::getDHSdata |
A partially processed data.frame that will be used in survryPrev::getDHSindicator. The whole function can be used as a parameter in survryPrev::getDHSindicator
Miaolei Bao, Yunhan Wu, Qianyu Dong
HC_FLRM_H_CER Percentage of households with ceramic tile floors ph_floor in github HR
HC_FLRM_H_CER(Rdata)HC_FLRM_H_CER(Rdata)
Rdata |
data.frame from survryPrev::getDHSdata |
A partially processed data.frame that will be used in survryPrev::getDHSindicator. The whole function can be used as a parameter in survryPrev::getDHSindicator
Miaolei Bao, Yunhan Wu, Qianyu Dong
HC_HEFF_H_RDO Percentage of households possessing a radio ph_radio in github HR
HC_HEFF_H_RDO(Rdata)HC_HEFF_H_RDO(Rdata)
Rdata |
data.frame from survryPrev::getDHSdata |
A partially processed data.frame that will be used in survryPrev::getDHSindicator. The whole function can be used as a parameter in survryPrev::getDHSindicator
Miaolei Bao, Yunhan Wu, Qianyu Dong
HA_HIVP_W_HIV hv_hiv_pos "HIV positive test result"
hv_hiv_pos(Rdata)hv_hiv_pos(Rdata)
Rdata |
data.frame from survryPrev::getDHSdata |
A partially processed data.frame that will be used in survryPrev::getDHSindicator. The whole function can be used as a parameter in survryPrev::getDHSindicator
Qianyu Dong
## Not run: dhsData <- getDHSdata(country = "Zambia", indicator = "HA_HIVP_W_HIV", year = 2018) data <- getDHSindicator(dhsData, indicator = NULL, FUN = surveyPrev::hv_hiv_pos) ## End(Not run)## Not run: dhsData <- getDHSdata(country = "Zambia", indicator = "HA_HIVP_W_HIV", year = 2018) data <- getDHSindicator(dhsData, indicator = NULL, FUN = surveyPrev::hv_hiv_pos) ## End(Not run)
This function return scatter plot at admin 1 level for any two model results
intervalPlot( admin = 0, compare = FALSE, model = NULL, group = FALSE, sort_by = NULL, decreasing = FALSE )intervalPlot( admin = 0, compare = FALSE, model = NULL, group = FALSE, sort_by = NULL, decreasing = FALSE )
admin |
level of plot |
compare |
plot for compare multiple plot or not |
model |
list of model results using surveyPrev |
group |
plot by group or not |
sort_by |
the name of the model to sort the areas by. Default to be NULL |
decreasing |
whether the regions are sorted in decreasing order. Default to be NULL |
This function returns the dataset that contain district name and population for given tiff files and polygons of admin level.
Qianyu Dong
## Not run: geo <- getDHSgeo(country = "Zambia", year = 2018) data(ZambiaAdm1) data(ZambiaAdm2) data(ZambiaPopWomen) cluster.info <- clusterInfo(geo = geo, poly.adm1 = ZambiaAdm1, poly.adm2 = ZambiaAdm2) dhsData <- getDHSdata(country = "Zambia", indicator = "ancvisit4+", year = 2018) data <- getDHSindicator(dhsData, indicator = "ancvisit4+") admin.info2 <- adminInfo(poly.adm = ZambiaAdm2, admin = 2, agg.pop =ZambiaPopWomen$admin2_pop, proportion = ZambiaPopWomen$admin2_urban) cl_res_ad2_unstrat <- clusterModel(data = data, cluster.info = cluster.info, admin.info = admin.info2, stratification = FALSE, model = "bym2", admin = 2, aggregation = TRUE, CI = 0.95) head(cl_res_ad2_unstrat$res.admin2) head(cl_res_ad2_unstrat$agg.admin1) plots <- intervalPlot(cl_res_ad2_unstrat) plots[["Central"]] cl_res_ad2 <- clusterModel(data = data, cluster.info = cluster.info, admin.info = admin.info2, stratification = TRUE, model = "bym2", admin = 2, aggregation = TRUE, CI = 0.95) head(cl_res_ad2$res.admin2) head(cl_res_ad2$agg.admin1) plots <- intervalPlot(cl_res_ad2) plots[["Central"]] library(patchwork) wrap_plots(plots, ncol = 5) ## End(Not run)## Not run: geo <- getDHSgeo(country = "Zambia", year = 2018) data(ZambiaAdm1) data(ZambiaAdm2) data(ZambiaPopWomen) cluster.info <- clusterInfo(geo = geo, poly.adm1 = ZambiaAdm1, poly.adm2 = ZambiaAdm2) dhsData <- getDHSdata(country = "Zambia", indicator = "ancvisit4+", year = 2018) data <- getDHSindicator(dhsData, indicator = "ancvisit4+") admin.info2 <- adminInfo(poly.adm = ZambiaAdm2, admin = 2, agg.pop =ZambiaPopWomen$admin2_pop, proportion = ZambiaPopWomen$admin2_urban) cl_res_ad2_unstrat <- clusterModel(data = data, cluster.info = cluster.info, admin.info = admin.info2, stratification = FALSE, model = "bym2", admin = 2, aggregation = TRUE, CI = 0.95) head(cl_res_ad2_unstrat$res.admin2) head(cl_res_ad2_unstrat$agg.admin1) plots <- intervalPlot(cl_res_ad2_unstrat) plots[["Central"]] cl_res_ad2 <- clusterModel(data = data, cluster.info = cluster.info, admin.info = admin.info2, stratification = TRUE, model = "bym2", admin = 2, aggregation = TRUE, CI = 0.95) head(cl_res_ad2$res.admin2) head(cl_res_ad2$agg.admin1) plots <- intervalPlot(cl_res_ad2) plots[["Central"]] library(patchwork) wrap_plots(plots, ncol = 5) ## End(Not run)
MA_CWIV_W_CWV
MA_CWIV_W_CWV(IRdata)MA_CWIV_W_CWV(IRdata)
IRdata |
data.frame from survryPrev::getDHSdata |
A partially processed data.frame that will be used in survryPrev::getDHSindicator. The whole function can be used as a parameter in survryPrev::getDHSindicator
Miaolei Bao, Yunhan Wu, Qianyu Dong
MA_MBAG_W_B15 Women first married by exact age 15 ms_afm_15 in github IR
MA_MBAG_W_B15(Rdata)MA_MBAG_W_B15(Rdata)
Rdata |
data.frame from survryPrev::getDHSdata |
A partially processed data.frame that will be used in survryPrev::getDHSindicator. The whole function can be used as a parameter in survryPrev::getDHSindicator
Miaolei Bao, Yunhan Wu, Qianyu Dong
##' MA_MBAG_W_B18 Percentage of women first married by exact age 18 ms_afm_18 in github IR
MA_MBAG_W_B18(Rdata)MA_MBAG_W_B18(Rdata)
Rdata |
data.frame from survryPrev::getDHSdata |
A partially processed data.frame that will be used in survryPrev::getDHSindicator. The whole function can be used as a parameter in survryPrev::getDHSindicator
Miaolei Bao, Yunhan Wu, Qianyu Dong
MA_MBAY_W_B15 Young women age 20-24 first married by exact age 15 ms_afm_15 in github IR
MA_MBAY_W_B15(Rdata)MA_MBAY_W_B15(Rdata)
Rdata |
data.frame from survryPrev::getDHSdata |
A partially processed data.frame that will be used in survryPrev::getDHSindicator. The whole function can be used as a parameter in survryPrev::getDHSindicator
Miaolei Bao, Yunhan Wu, Qianyu Dong
MA_MBAY_W_B18 Percentage of Young women age 20-24 first married by exact age 18 ms_afm_18 in github IR
MA_MBAY_W_B18(Rdata)MA_MBAY_W_B18(Rdata)
Rdata |
data.frame from survryPrev::getDHSdata |
A partially processed data.frame that will be used in survryPrev::getDHSindicator. The whole function can be used as a parameter in survryPrev::getDHSindicator
Miaolei Bao, Yunhan Wu, Qianyu Dong
MA_MSTA_W_NMA
MA_MSTA_W_NMA(IRdata)MA_MSTA_W_NMA(IRdata)
IRdata |
data.frame from survryPrev::getDHSdata |
A partially processed data.frame that will be used in survryPrev::getDHSindicator. The whole function can be used as a parameter in survryPrev::getDHSindicator
Miaolei Bao, Yunhan Wu, Qianyu Dong
ML_ITNA_P_ACC Households with at least one insecticide-treated mosquito net (ITN) for every two persons who stayed in the household the previous night Persons with access to an insecticide-treated mosquito net (ITN) ML_NETS_HH.do HR Households with >1 ITN per 2 household members Percentage of households with at least one ITN for every 2 persons who stayed in the household last night
ml_hhaccess(Rdata)ml_hhaccess(Rdata)
Rdata |
data.frame from survryPrev::getDHSdata |
A partially processed data.frame that will be used in survryPrev::getDHSindicator. The whole function can be used as a parameter in survryPrev::getDHSindicator
Qianyu Dong
## Not run: dhsData <- getDHSdata(country = "Zambia", indicator = "ML_ITNA_P_ACC", year = 2018) data <- getDHSindicator(dhsData, indicator = NULL, FUN = surveyPrev::ml_hhaccess) ## End(Not run)## Not run: dhsData <- getDHSdata(country = "Zambia", indicator = "ML_ITNA_P_ACC", year = 2018) data <- getDHSindicator(dhsData, indicator = NULL, FUN = surveyPrev::ml_hhaccess) ## End(Not run)
CM_ECMR_C_NNR nmr CM_ECMR_C_NNR BR (not from dhs github) Neonatal mortality rate !!!!!!
NMR(Rdata, nmr.year)NMR(Rdata, nmr.year)
Rdata |
data.frame from survryPrev::getDHSdata |
nmr.year |
This is an argument specifically for NMR calculation. It specifies births how many years do we include prior to the date of survey. Default to be 10, i.e., NMR in the last 10 years prior to survey. |
A partially processed data.frame that will be used in survryPrev::getDHSindicator. The whole function can be used as a parameter in survryPrev::getDHSindicator
Qianyu Dong
## Not run: dhsData <- getDHSdata(country = "Zambia", indicator = "CM_ECMR_C_NNR", year = 2018) data <- getDHSindicator(dhsData, indicator = NULL, FUN = surveyPrev::NMR) ## End(Not run)## Not run: dhsData <- getDHSdata(country = "Zambia", indicator = "CM_ECMR_C_NNR", year = 2018) data <- getDHSindicator(dhsData, indicator = NULL, FUN = surveyPrev::NMR) ## End(Not run)
CN_ANMC_C_ANY Children with any anemia "Any anemia - child 6-59 months" PR NT_CH_NUT.do Children under five with any anemia
nt_ch_any_anem(Rdata)nt_ch_any_anem(Rdata)
Rdata |
data.frame from survryPrev::getDHSdata |
A partially processed data.frame that will be used in survryPrev::getDHSindicator. The whole function can be used as a parameter in survryPrev::getDHSindicator
Qianyu Dong
## Not run: dhsData <- getDHSdata(country = "Zambia", indicator = "CN_ANMC_C_ANY", year = 2018) data <- getDHSindicator(dhsData, indicator = NULL, FUN = surveyPrev::nt_ch_any_anem) ## End(Not run)## Not run: dhsData <- getDHSdata(country = "Zambia", indicator = "CN_ANMC_C_ANY", year = 2018) data <- getDHSindicator(dhsData, indicator = NULL, FUN = surveyPrev::nt_ch_any_anem) ## End(Not run)
CN_NUTS_C_HA2 stunting Children stunted NT_CH_NUT.do PR "Stunted child under 5 years" Stunting rate (Prevalence of stunted (HAZ < -2) children under five (0-59 months)) Percentage of children under age five stunted (below -2 standard deviations of height-for-age according to the WHO standard).
nt_ch_stunt(Rdata)nt_ch_stunt(Rdata)
Rdata |
data.frame from survryPrev::getDHSdata |
A partially processed data.frame that will be used in survryPrev::getDHSindicator. The whole function can be used as a parameter in survryPrev::getDHSindicator
Qianyu Dong
## Not run: dhsData <- getDHSdata(country = "Zambia", indicator = "CN_NUTS_C_HA2", year = 2018) data <- getDHSindicator(dhsData, indicator = NULL, FUN = surveyPrev::nt_ch_stunt) ## End(Not run)## Not run: dhsData <- getDHSdata(country = "Zambia", indicator = "CN_NUTS_C_HA2", year = 2018) data <- getDHSindicator(dhsData, indicator = NULL, FUN = surveyPrev::nt_ch_stunt) ## End(Not run)
CN_NUTS_C_WH2 wasting Children wasted NT_CH_NUT.do PR "Wasted child under 5 years" Wasting rate (Prevalence of wasted (HAZ < -2) children under five (0-59 months)) Percentage of children under age five with a weight-for-height z-score (WHZ) more than two standard deviations below the median WHO growth standards.
nt_ch_wast(Rdata)nt_ch_wast(Rdata)
Rdata |
data.frame from survryPrev::getDHSdata |
A partially processed data.frame that will be used in survryPrev::getDHSindicator. The whole function can be used as a parameter in survryPrev::getDHSindicator
Qianyu Dong
## Not run: dhsData <- getDHSdata(country = "Zambia", indicator = "CN_NUTS_C_WH2", year = 2018) data <- getDHSindicator(dhsData, indicator = NULL, FUN = surveyPrev::nt_ch_wast) ## End(Not run)## Not run: dhsData <- getDHSdata(country = "Zambia", indicator = "CN_NUTS_C_WH2", year = 2018) data <- getDHSindicator(dhsData, indicator = NULL, FUN = surveyPrev::nt_ch_wast) ## End(Not run)
CN_BRFS_C_EXB Children exclusively breastfed NT_IYCF.do KR "Exclusively breastfed - last-born under 6 months" Children exclusively breastfed (Prevalence of exclusive breastfeeding of children under six months of age)
nt_ebf(Rdata)nt_ebf(Rdata)
Rdata |
data.frame from survryPrev::getDHSdata |
A partially processed data.frame that will be used in survryPrev::getDHSindicator. The whole function can be used as a parameter in survryPrev::getDHSindicator
Qianyu Dong
## Not run: dhsData <- getDHSdata(country = "Zambia", indicator = "CN_BRFS_C_EXB", year = 2018) data <- getDHSindicator(dhsData, indicator = NULL, FUN = surveyPrev::nt_ebf) ## End(Not run)## Not run: dhsData <- getDHSdata(country = "Zambia", indicator = "CN_BRFS_C_EXB", year = 2018) data <- getDHSindicator(dhsData, indicator = NULL, FUN = surveyPrev::nt_ebf) ## End(Not run)
AN_ANEM_W_ANY womananemia nt_wm_any_anem "Any anemia - women" NT_WM_NUT.do Percentage of women aged 15-49 classified as having any anemia
nt_wm_any_anem(Rdata)nt_wm_any_anem(Rdata)
Rdata |
data.frame from survryPrev::getDHSdata |
A partially processed data.frame that will be used in survryPrev::getDHSindicator. The whole function can be used as a parameter in survryPrev::getDHSindicator
Qianyu Dong
## Not run: dhsData <- getDHSdata(country = "Zambia", indicator = "AN_ANEM_W_ANY", year = 2018) data <- getDHSindicator(dhsData, indicator = NULL, FUN = surveyPrev::nt_wm_any_anem) ## End(Not run)## Not run: dhsData <- getDHSdata(country = "Zambia", indicator = "AN_ANEM_W_ANY", year = 2018) data <- getDHSindicator(dhsData, indicator = NULL, FUN = surveyPrev::nt_wm_any_anem) ## End(Not run)
AN_NUTS_W_THN Women who are thin according to BMI (<18.5) NT_WM_NUT.do "Thin BMI - women" IR !!!!!!!! Underweight (Prevalence of underweight (BMI < 18.5) women of reproductive age)
nt_wm_thin(Rdata)nt_wm_thin(Rdata)
Rdata |
data.frame from survryPrev::getDHSdata |
A partially processed data.frame that will be used in survryPrev::getDHSindicator. The whole function can be used as a parameter in survryPrev::getDHSindicator
Qianyu Dong
## Not run: dhsData <- getDHSdata(country = "Zambia", indicator = "AN_NUTS_W_THN", year = 2018) data <- getDHSindicator(dhsData, indicator = NULL, FUN = surveyPrev::nt_wm_thin) ## End(Not run)## Not run: dhsData <- getDHSdata(country = "Zambia", indicator = "AN_NUTS_W_THN", year = 2018) data <- getDHSindicator(dhsData, indicator = NULL, FUN = surveyPrev::nt_wm_thin) ## End(Not run)
WS_TLET_P_BAS Population with access to a basic sanitation service WS_TLET_P_BAS in DHS API PH_SANI.do PR ph_sani_basic "Basic sanitation facility"
ph_sani_basic(Rdata)ph_sani_basic(Rdata)
Rdata |
data.frame from survryPrev::getDHSdata |
A partially processed data.frame that will be used in survryPrev::getDHSindicator. The whole function can be used as a parameter in survryPrev::getDHSindicator
Qianyu Dong
## Not run: dhsData <- getDHSdata(country = "Zambia", indicator = "WS_TLET_P_BAS", year = 2018) data <- getDHSindicator(dhsData, indicator = NULL, FUN = surveyPrev::ph_sani_basic) ## End(Not run)## Not run: dhsData <- getDHSdata(country = "Zambia", indicator = "WS_TLET_P_BAS", year = 2018) data <- getDHSindicator(dhsData, indicator = NULL, FUN = surveyPrev::ph_sani_basic) ## End(Not run)
WS_TLET_H_IMP Percentage of households using an improved sanitation facility PH_SANI.do PR ph_sani_improve "Access to improved sanitation" country-specific
ph_sani_improve(Rdata)ph_sani_improve(Rdata)
Rdata |
data.frame from survryPrev::getDHSdata |
A partially processed data.frame that will be used in survryPrev::getDHSindicator. The whole function can be used as a parameter in survryPrev::getDHSindicator
Qianyu Dong
## Not run: dhsData <- getDHSdata(country = "Zambia", indicator = "WS_TLET_H_IMP", year = 2018) data <- getDHSindicator(dhsData, indicator = NULL, FUN = surveyPrev::ph_sani_improve) ## End(Not run)## Not run: dhsData <- getDHSdata(country = "Zambia", indicator = "WS_TLET_H_IMP", year = 2018) data <- getDHSindicator(dhsData, indicator = NULL, FUN = surveyPrev::ph_sani_improve) ## End(Not run)
PR_DESL_W_WNM
PR_DESL_W_WNM(IRdata)PR_DESL_W_WNM(IRdata)
IRdata |
data.frame from survryPrev::getDHSdata |
A partially processed data.frame that will be used in survryPrev::getDHSindicator. The whole function can be used as a parameter in survryPrev::getDHSindicator
Miaolei Bao, Yunhan Wu, Qianyu Dong
This function return scatter plot at admin 1 or 2 level for given model results.
rankPlot(x, direction = 1)rankPlot(x, direction = 1)
x |
a model result using surveyPrev of class "fhModel" or "clusterModel" |
direction |
direction of the ranking. The default is direction = 1, which correspond to larger value having higher ranking. If direction = -1, larger value has lower ranking. |
This function returns a ranking plot.
Zehang Li, Qianyu Dong
## Not run: geo <- getDHSgeo(country = "Zambia", year = 2018) data(ZambiaAdm1) data(ZambiaAdm2) data(ZambiaPopWomen) cluster.info <- clusterInfo(geo = geo, poly.adm1 = ZambiaAdm1, poly.adm2 = ZambiaAdm2) dhsData <- getDHSdata(country = "Zambia", indicator = "ancvisit4+", year = 2018) data <- getDHSindicator(dhsData, indicator = "ancvisit4+") admin.info2 <- adminInfo(poly.adm = ZambiaAdm2, admin = 2, by.adm="NAME_2", by.adm.upper = "NAME_1") cl_res_ad2_unstrat <- clusterModel(data = data, cluster.info = cluster.info, admin.info = admin.info2, stratification = FALSE, model = "bym2", admin = 2, aggregation = TRUE, CI = 0.95) rankPlot(cl_res_ad2_unstrat) ## End(Not run)## Not run: geo <- getDHSgeo(country = "Zambia", year = 2018) data(ZambiaAdm1) data(ZambiaAdm2) data(ZambiaPopWomen) cluster.info <- clusterInfo(geo = geo, poly.adm1 = ZambiaAdm1, poly.adm2 = ZambiaAdm2) dhsData <- getDHSdata(country = "Zambia", indicator = "ancvisit4+", year = 2018) data <- getDHSindicator(dhsData, indicator = "ancvisit4+") admin.info2 <- adminInfo(poly.adm = ZambiaAdm2, admin = 2, by.adm="NAME_2", by.adm.upper = "NAME_1") cl_res_ad2_unstrat <- clusterModel(data = data, cluster.info = cluster.info, admin.info = admin.info2, stratification = FALSE, model = "bym2", admin = 2, aggregation = TRUE, CI = 0.95) rankPlot(cl_res_ad2_unstrat) ## End(Not run)
RH_ANCN_W_N4P ancvisit4+ RH_ANCN_W_N4P IR Antenatal visits for pregnancy: 4+ visits
rh_anc_4vs(Rdata)rh_anc_4vs(Rdata)
Rdata |
data.frame from survryPrev::getDHSdata |
A partially processed data.frame that will be used in survryPrev::getDHSindicator. The whole function can be used as a parameter in survryPrev::getDHSindicator
Qianyu Dong
## Not run: dhsData <- getDHSdata(country = "Zambia", indicator = "RH_ANCN_W_N4P", year = 2018) data <- getDHSindicator(dhsData, indicator = NULL, FUN = surveyPrev::rh_anc_4vs) ## End(Not run)## Not run: dhsData <- getDHSdata(country = "Zambia", indicator = "RH_ANCN_W_N4P", year = 2018) data <- getDHSindicator(dhsData, indicator = NULL, FUN = surveyPrev::rh_anc_4vs) ## End(Not run)
AH_TOBC_W_OTH
RH_ANCN_W_N01(Rdata)RH_ANCN_W_N01(Rdata)
Rdata |
data.frame from survryPrev::getDHSdata |
A partially processed data.frame that will be used in survryPrev::getDHSindicator. The whole function can be used as a parameter in survryPrev::getDHSindicator
Miaolei Bao, Yunhan Wu, Qianyu Dong
RH_DELA_C_SKP IR or BR Assistance during delivery from a skilled provider
rh_del_pvskill(Rdata)rh_del_pvskill(Rdata)
Rdata |
data.frame from survryPrev::getDHSdata |
A partially processed data.frame that will be used in survryPrev::getDHSindicator. The whole function can be used as a parameter in survryPrev::getDHSindicator
Qianyu Dong
## Not run: dhsData <- getDHSdata(country = "Zambia", indicator = "RH_DELA_C_SKP", year = 2018) data <- getDHSindicator(dhsData, indicator = NULL, FUN = surveyPrev::rh_del_pvskill) ## End(Not run)## Not run: dhsData <- getDHSdata(country = "Zambia", indicator = "RH_DELA_C_SKP", year = 2018) data <- getDHSindicator(dhsData, indicator = NULL, FUN = surveyPrev::rh_del_pvskill) ## End(Not run)
RH_DELP_C_DHF
RH_DELP_C_DHF(Rdata)RH_DELP_C_DHF(Rdata)
Rdata |
data.frame from survryPrev::getDHSdata |
A partially processed data.frame that will be used in survryPrev::getDHSindicator. The whole function can be used as a parameter in survryPrev::getDHSindicator
Miaolei Bao, Yunhan Wu, Qianyu Dong
RH_PCCT_C_DY2 Newborn's first postnatal checkup: 1-2 days rh_pnc_nb_2days in github IR
RH_PCCT_C_DY2(Rdata)RH_PCCT_C_DY2(Rdata)
Rdata |
data.frame from survryPrev::getDHSdata |
A partially processed data.frame that will be used in survryPrev::getDHSindicator. The whole function can be used as a parameter in survryPrev::getDHSindicator
Miaolei Bao, Yunhan Wu, Qianyu Dong
This function return scatter plot at admin 1 level for any two model results
scatterPlot( res1, value1, res2, value2, label1, label2, by.res1, by.res2, title )scatterPlot( res1, value1, res2, value2, label1, label2, by.res1, by.res2, title )
res1 |
model result 1 using surveyPrev |
value1 |
value1 |
res2 |
model result 2 using surveyPrev |
value2 |
value2 |
label1 |
label for x axis |
label2 |
label for y axis |
by.res1 |
by.res1 |
by.res2 |
by.res2 |
title |
title |
This function returns the dataset that contain district name and population for given tiff files and polygons of admin level
Qianyu Dong
## Not run: geo <- getDHSgeo(country = "Zambia", year = 2018) data(ZambiaAdm1) data(ZambiaAdm2) data(ZambiaPopWomen) cluster.info <- clusterInfo(geo = geo, poly.adm1 = ZambiaAdm1, poly.adm2 = ZambiaAdm2) dhsData <- getDHSdata(country = "Zambia", indicator = "ancvisit4+", year = 2018) data <- getDHSindicator(dhsData, indicator = "ancvisit4+") admin.info1 <- adminInfo(poly.adm = ZambiaAdm1, admin = 1, agg.pop =ZambiaPopWomen$admin1_pop, proportion = ZambiaPopWomen$admin1_urban) smth_res_ad1 <- fhModel(data, cluster.info = cluster.info, admin.info = admin.info1, admin = 1, model = "bym2", aggregation = F) admin.info2 <- adminInfo(poly.adm = ZambiaAdm2, admin = 2, agg.pop =ZambiaPopWomen$admin2_pop, proportion = ZambiaPopWomen$admin2_urban) cl_res_ad2 <- clusterModel(data = data, cluster.info = cluster.info, admin.info = admin.info2, stratification = FALSE, model = "bym2", admin = 2, aggregation = TRUE, CI = 0.95) scatterPlot( res1 = smth_res_ad1, res2 = cl_res_ad2$agg.admin1, value1 = "value", value2 = "value", by.res1 = "admin1.name", by.res2 = "admin1.name", title = "Aggregated cluster model v.s. Fay–Herriot", label1 = "Fay–Herriot", label2 = "Aggregated cluster model") ## End(Not run)## Not run: geo <- getDHSgeo(country = "Zambia", year = 2018) data(ZambiaAdm1) data(ZambiaAdm2) data(ZambiaPopWomen) cluster.info <- clusterInfo(geo = geo, poly.adm1 = ZambiaAdm1, poly.adm2 = ZambiaAdm2) dhsData <- getDHSdata(country = "Zambia", indicator = "ancvisit4+", year = 2018) data <- getDHSindicator(dhsData, indicator = "ancvisit4+") admin.info1 <- adminInfo(poly.adm = ZambiaAdm1, admin = 1, agg.pop =ZambiaPopWomen$admin1_pop, proportion = ZambiaPopWomen$admin1_urban) smth_res_ad1 <- fhModel(data, cluster.info = cluster.info, admin.info = admin.info1, admin = 1, model = "bym2", aggregation = F) admin.info2 <- adminInfo(poly.adm = ZambiaAdm2, admin = 2, agg.pop =ZambiaPopWomen$admin2_pop, proportion = ZambiaPopWomen$admin2_urban) cl_res_ad2 <- clusterModel(data = data, cluster.info = cluster.info, admin.info = admin.info2, stratification = FALSE, model = "bym2", admin = 2, aggregation = TRUE, CI = 0.95) scatterPlot( res1 = smth_res_ad1, res2 = cl_res_ad2$agg.admin1, value1 = "value", value2 = "value", by.res1 = "admin1.name", by.res2 = "admin1.name", title = "Aggregated cluster model v.s. Fay–Herriot", label1 = "Fay–Herriot", label2 = "Aggregated cluster model") ## End(Not run)
A data frame of indicators currently implemented in the package
data(surveyPrevIndicators)data(surveyPrevIndicators)
An object of class data.frame with 22 rows and 4 columns.
WS_SRCE_P_BAS Population using a basic water source PH_WATER.do ph_wtr_basic "Basic water service" PR
watersource_adj(Rdata)watersource_adj(Rdata)
Rdata |
data.frame from survryPrev::getDHSdata |
A partially processed data.frame that will be used in survryPrev::getDHSindicator. The whole function can be used as a parameter in survryPrev::getDHSindicator
Qianyu Dong
## Not run: dhsData <- getDHSdata(country = "Zambia", indicator = "WS_SRCE_P_BAS", year = 2018) data <- getDHSindicator(dhsData, indicator = NULL, FUN = surveyPrev::watersource_adj) ## End(Not run)## Not run: dhsData <- getDHSdata(country = "Zambia", indicator = "WS_SRCE_P_BAS", year = 2018) data <- getDHSindicator(dhsData, indicator = NULL, FUN = surveyPrev::watersource_adj) ## End(Not run)
WE_AWBT_M_ARG
WE_AWBT_M_ARG(MRdata)WE_AWBT_M_ARG(MRdata)
MRdata |
data.frame from survryPrev::getDHSdata |
A partially processed data.frame that will be used in survryPrev::getDHSindicator. The whole function can be used as a parameter in survryPrev::getDHSindicator
Miaolei Bao, Yunhan Wu, Qianyu Dong
WE_AWBT_M_BFD
WE_AWBT_M_BFD(MRdata)WE_AWBT_M_BFD(MRdata)
MRdata |
data.frame from survryPrev::getDHSdata |
A partially processed data.frame that will be used in survryPrev::getDHSindicator. The whole function can be used as a parameter in survryPrev::getDHSindicator
Miaolei Bao, Yunhan Wu, Qianyu Dong
WE_AWBT_M_OUT
WE_AWBT_M_OUT(MRdata)WE_AWBT_M_OUT(MRdata)
MRdata |
data.frame from survryPrev::getDHSdata |
A partially processed data.frame that will be used in survryPrev::getDHSindicator. The whole function can be used as a parameter in survryPrev::getDHSindicator
Miaolei Bao, Yunhan Wu, Qianyu Dong
WE_AWBT_M_REF
WE_AWBT_M_REF(MRdata)WE_AWBT_M_REF(MRdata)
MRdata |
data.frame from survryPrev::getDHSdata |
A partially processed data.frame that will be used in survryPrev::getDHSindicator. The whole function can be used as a parameter in survryPrev::getDHSindicator
Miaolei Bao, Yunhan Wu, Qianyu Dong
WE_AWBT_W_ARG
WE_AWBT_W_ARG(IRdata)WE_AWBT_W_ARG(IRdata)
IRdata |
data.frame from survryPrev::getDHSdata |
A partially processed data.frame that will be used in survryPrev::getDHSindicator. The whole function can be used as a parameter in survryPrev::getDHSindicator
Miaolei Bao, Yunhan Wu, Qianyu Dong
WE_AWBT_W_BFD
WE_AWBT_W_BFD(IRdata)WE_AWBT_W_BFD(IRdata)
IRdata |
data.frame from survryPrev::getDHSdata |
A partially processed data.frame that will be used in survryPrev::getDHSindicator. The whole function can be used as a parameter in survryPrev::getDHSindicator
Miaolei Bao, Yunhan Wu, Qianyu Dong
WE_AWBT_W_NEG
WE_AWBT_W_NEG(IRdata)WE_AWBT_W_NEG(IRdata)
IRdata |
data.frame from survryPrev::getDHSdata |
A partially processed data.frame that will be used in survryPrev::getDHSindicator. The whole function can be used as a parameter in survryPrev::getDHSindicator
Miaolei Bao, Yunhan Wu, Qianyu Dong
WE_AWBT_W_OUT
WE_AWBT_W_OUT(IRdata)WE_AWBT_W_OUT(IRdata)
IRdata |
data.frame from survryPrev::getDHSdata |
A partially processed data.frame that will be used in survryPrev::getDHSindicator. The whole function can be used as a parameter in survryPrev::getDHSindicator
Miaolei Bao, Yunhan Wu, Qianyu Dong
WE_AWBT_W_REF
WE_AWBT_W_REF(IRdata)WE_AWBT_W_REF(IRdata)
IRdata |
data.frame from survryPrev::getDHSdata |
A partially processed data.frame that will be used in survryPrev::getDHSindicator. The whole function can be used as a parameter in survryPrev::getDHSindicator
Miaolei Bao, Yunhan Wu, Qianyu Dong
WS_SRCE_H_USG Percentage of households whose main source of drinking water is an unprotected spring ph_wtr_source in github "unprotected spring" = 42, HR
WS_SRCE_H_USG(Rdata)WS_SRCE_H_USG(Rdata)
Rdata |
data.frame from survryPrev::getDHSdata |
A partially processed data.frame that will be used in survryPrev::getDHSindicator. The whole function can be used as a parameter in survryPrev::getDHSindicator
Miaolei Bao, Yunhan Wu, Qianyu Dong
WS_WTRT_P_BLC
WS_WTRT_P_BLC(WASHdata)WS_WTRT_P_BLC(WASHdata)
WASHdata |
data.frame from survryPrev::getDHSdata |
A partially processed data.frame that will be used in survryPrev::getDHSindicator. The whole function can be used as a parameter in survryPrev::getDHSindicator
Miaolei Bao, Yunhan Wu, Qianyu Dong
WS_WTRT_P_BOL
WS_WTRT_P_BOL(WASHdata)WS_WTRT_P_BOL(WASHdata)
WASHdata |
data.frame from survryPrev::getDHSdata |
A partially processed data.frame that will be used in survryPrev::getDHSindicator. The whole function can be used as a parameter in survryPrev::getDHSindicator
Miaolei Bao, Yunhan Wu, Qianyu Dong
WS_WTRT_P_SOL
WS_WTRT_P_SOL(WASHdata)WS_WTRT_P_SOL(WASHdata)
WASHdata |
data.frame from survryPrev::getDHSdata |
A partially processed data.frame that will be used in survryPrev::getDHSindicator. The whole function can be used as a parameter in survryPrev::getDHSindicator
Miaolei Bao, Yunhan Wu, Qianyu Dong
WS_WTRT_P_STN
WS_WTRT_P_STN(WASHdata)WS_WTRT_P_STN(WASHdata)
WASHdata |
data.frame from survryPrev::getDHSdata |
A partially processed data.frame that will be used in survryPrev::getDHSindicator. The whole function can be used as a parameter in survryPrev::getDHSindicator
Miaolei Bao, Yunhan Wu, Qianyu Dong
A SpatialPolygonsDataFrame corresponding to Zambia's admin-1 regions. The dataset is downloaded from GADM (https://gadm.org/data.html) version 4.1.
data(ZambiaAdm1)data(ZambiaAdm1)
An object of class SpatialPolygonsDataFrame with 10 rows and 11 columns.
A SpatialPolygonsDataFrame corresponding to Zambia's admin-2 regions. The dataset is downloaded from GADM (https://gadm.org/data.html) version 4.1.
data(ZambiaAdm2)data(ZambiaAdm2)
An object of class SpatialPolygonsDataFrame with 115 rows and 13 columns.
A list of three objects
raster A 100m by 100m raster file for the population estimates for women of age 15 to 49 in Zambia in 2018
admin1_urban A data frame specifying the proportion of urban population (as defined by those living in regions designated as urban in the previous census) for Women of age 15 to 49 in Zambia in 2018, in each admin1 region.
admin2_urban A data frame specifying the proportion of urban population (as defined by those living in regions designated as urban in the previous census) for Women of age 15 to 49 in Zambia in 2018, in each admin2 region. The corresponding admin1 region name is also included.
The dataset is downloaded from WorldPop (https://hub.worldpop.org/geodata/summary?id=16429) and post processed.
data(ZambiaPopWomen)data(ZambiaPopWomen)
An object of class list of length 4.