CM_ECMR_C_NNR nmr CM_ECMR_C_NNR BR (not from dhs github) Neonatal mortality rate !!!!!!

Description

CM_ECMR_C_NNR nmr CM_ECMR_C_NNR BR (not from dhs github) Neonatal mortality rate !!!!!!

Usage

NMR(Rdata)

Arguments

Value

A partially processed data.frame that will be used in survryPrev::getDHSindicator. The whole function can be used as a parameter in survryPrev::getDHSindicator

Author(s)

Qianyu Dong

Examples

## Not run: 
dhsData <- getDHSdata(country = "Zambia",
                                 indicator = "CM_ECMR_C_NNR",
                                 year = 2018)
data <- getDHSindicator(dhsData, indicator = NULL,
                         FUN = surveyPrev::NMR)

## End(Not run)

Admin 1 Polygon Map for Zambia.

Description

A SpatialPolygonsDataFrame corresponding to Zambia's admin-1 regions. The dataset is downloaded from GADM (https://gadm.org/data.html) version 4.1.

Usage

data(ZambiaAdm1)

Format

An object of class SpatialPolygonsDataFrame with 10 rows and 11 columns.

Admin 2 Polygon Map for Zambia.

Description

A SpatialPolygonsDataFrame corresponding to Zambia's admin-2 regions. The dataset is downloaded from GADM (https://gadm.org/data.html) version 4.1.

Usage

data(ZambiaAdm2)

Format

An object of class SpatialPolygonsDataFrame with 115 rows and 13 columns.

Population estimates for Women of age 15 to 49 in Zambia in 2018.

Description

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.

Usage

data(ZambiaPopWomen)

Format

An object of class list of length 4.

Get admin information

Description

This function get admin information including name, character, population and unban/rural proportion.

Usage

adminInfo(
  poly.adm,
  by.adm,
  admin,
  by.adm.upper = NULL,
  agg.pop = NULL,
  proportion = NULL
)

Arguments

Value

This function returns the 1. dataframe that contains admin 1 and admin 2 information and coordinates for each cluster and 2. Adjacency matrix.

Author(s)

Qianyu Dong

Examples

# 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 )

Get population information

Description

This function aggregate population to particular admin levels

Usage

aggPopulation(tiff, fact = 10, poly.adm, by.adm, by.adm.upper = NULL)

Arguments

Value

This function returns the dataset that contain district name and population for given tiff files and polygons of admin level

Author(s)

Qianyu Dong

Examples

## 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)

Get survey weight by admin levels

Description

This function aggregate survey weight to particular admin levels

Usage

aggSurveyWeight(
  data,
  cluster.info,
  admin,
  poly.adm = NULL,
  by.adm = NULL,
  by.adm.upper = NULL
)

Arguments

Value

This function returns the dataset that contain admin name and survey weight.

Author(s)

Qianyu Dong

Examples

## 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)

CH_VACS_C_BAS Children with all 8 basic vaccinations (age 12-23) "All basic vaccinations according to either source"

Description

CH_VACS_C_BAS Children with all 8 basic vaccinations (age 12-23) "All basic vaccinations according to either source"

Usage

ch_allvac_either(Rdata)

Arguments

Value

A partially processed data.frame that will be used in survryPrev::getDHSindicator. The whole function can be used as a parameter in survryPrev::getDHSindicator

Author(s)

Qianyu Dong

Examples

## 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_DIAT_C_ORT KR Diarrhea treatment (Children under five with diarrhea treated with either ORS or RHF)

Description

CH_DIAT_C_ORT KR Diarrhea treatment (Children under five with diarrhea treated with either ORS or RHF)

Usage

ch_diar_ors_rhf(Rdata)

Arguments

Value

A partially processed data.frame that will be used in survryPrev::getDHSindicator. The whole function can be used as a parameter in survryPrev::getDHSindicator

Author(s)

Qianyu Dong

Examples

## 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_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"

Description

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"

Usage

ch_meas_either(Rdata)

Arguments

Value

A partially processed data.frame that will be used in survryPrev::getDHSindicator. The whole function can be used as a parameter in survryPrev::getDHSindicator

Author(s)

Qianyu Dong

Examples

## 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)

Description

CH_VACS_C_NON KR Children with no vaccinations (age 12-23)

Usage

ch_novac_either(Rdata)

Arguments

Value

A partially processed data.frame that will be used in survryPrev::getDHSindicator. The whole function can be used as a parameter in survryPrev::getDHSindicator

Author(s)

Qianyu Dong

Examples

## 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"

Description

CH_VACC_C_DP1 KR Percentage of children (age 12-23) Pentavalent 1rd dose vaccination according to either source"

Usage

ch_pent1_either(Rdata)

Arguments

Value

A partially processed data.frame that will be used in survryPrev::getDHSindicator. The whole function can be used as a parameter in survryPrev::getDHSindicator

Author(s)

Qianyu Dong

Examples

## 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"

Description

CH_VACC_C_DP3 DPT3 KR Percentage of children (age 12-23) Pentavalent 3rd dose vaccination according to either source"

Usage

ch_pent3_either(Rdata)

Arguments

Value

A partially processed data.frame that will be used in survryPrev::getDHSindicator. The whole function can be used as a parameter in survryPrev::getDHSindicator

Author(s)

Qianyu Dong

Examples

## 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)

Get cluster information

Description

This function add admin 1 and admin2 information to a paticular DHS survey.

Usage

clusterInfo(geo, poly.adm1, poly.adm2, by.adm1 = "NAME_1", by.adm2 = "NAME_2")

Arguments

Value

This function returns the dataset that contains admin 1 and admin 2 information and coordinates for each cluster.

Author(s)

Qianyu Dong

Examples

## 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)

Calculate cluster model estimates using beta binomial model

Description

This function calculate smoothed direct estimates at given admin level.

Usage

clusterModel(
  data,
  cluster.info,
  admin.info,
  admin,
  CI = 0.95,
  model = c("bym2", "iid"),
  stratification = FALSE,
  aggregation = FALSE,
  overdisp.mean = 0,
  overdisp.prec = 0.4
)

Arguments

Value

This function returns the dataset that contain district name and population for given tiff files and polygons of admin level,

Author(s)

Qianyu Dong

Examples

## 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)

Calculate direct estimates

Description

This function calculate direct estimates at given admin level.

Usage

directEST(
  data,
  cluster.info,
  admin,
  strata = "all",
  CI = 0.95,
  weight = c("population", "survey")[1],
  admin.info = NULL,
  aggregation = FALSE,
  ...
)

Arguments

Value

This function returns the dataset that contain district name and population for given tiff files and polygons of admin level,

Author(s)

Qianyu Dong

Examples

## Not run: 
geo <- getDHSgeo(country = "Zambia", year = 2018)
data(ZambiaAdm1)
data(ZambiaAdm2)
data(ZambiaPopWomen)
cluster.info<-clusterInfo(geo=geo, poly.adm1=poly.adm1, poly.adm2=poly.adm2,
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")


## End(Not run)

Calculate smoothed direct estimates

Description

This function calculate smoothed direct estimates at given admin level.

Usage

fhModel(
  data,
  cluster.info,
  admin.info = NULL,
  admin,
  CI = 0.95,
  model = c("bym2", "iid"),
  aggregation = FALSE
)

Arguments

Value

This function returns the dataset that contain district name and population for given tiff files and polygons of admin level,

Author(s)

Qianyu Dong

Examples

## 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)

Description

FP_CUSM_W_MOD IRdata Modern contraceptive prevalence rate (Married women currently using any modern method of contraception)

Usage

fp_cruse_mod(Rdata)

Arguments

Value

A partially processed data.frame that will be used in survryPrev::getDHSindicator. The whole function can be used as a parameter in survryPrev::getDHSindicator

Author(s)

Qianyu Dong

Examples

## Not run: 
dhsData <- getDHSdata(country = "Zambia",
                                 indicator = "FP_CUSM_W_MOD",
                                 year = 2018)
data <- getDHSindicator(dhsData, indicator = NULL,
                         FUN = surveyPrev::fp_cruse_mod)

## End(Not run)

FP_NADA_W_UNT #unmet_family IRdata women with an unmet need for family planning for spacing and limiting

Description

FP_NADA_W_UNT #unmet_family IRdata women with an unmet need for family planning for spacing and limiting

Usage

fp_unmet_tot(Rdata)

Arguments

Value

A partially processed data.frame that will be used in survryPrev::getDHSindicator. The whole function can be used as a parameter in survryPrev::getDHSindicator

Author(s)

Qianyu Dong

Examples

## 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)

Download DHS survey data

Description

This function downloads DHS data for a particular country and survey.

Usage

getDHSdata(country, indicator = NULL, Recode = NULL, year)

Arguments

Value

This function returns the survey dataset that contains the indicator.

Author(s)

Qianyu Dong

Examples

## 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)

Download DHS geo data

Description

This function downloads cluster's coordinate data for country and survey.

Usage

getDHSgeo(country, year)

Arguments

Value

The function returns a spatial point dataset with coordinates for each cluster based on the chosen survey and year.

Author(s)

Qianyu Dong

Examples

## Not run: 
geo <- getDHSgeo(country = "Zambia", year = 2018)

## End(Not run)

Process DHS data

Description

This function processes DHS data from getDHSdata function.

Usage

getDHSindicator(Rdata, indicator = NULL, FUN = NULL)

Arguments

Value

The function returns processed survey data that contains the indicator of interests.

Author(s)

Qianyu Dong

Examples

## 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")


## End(Not run)

Function to threshold population raster to obtain urban/rural fractions by Admin1 and Admin2 areas

Description

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.

Usage

getUR(
  tiff.census,
  tiff.survey,
  prop.census,
  fact = 10,
  poly.adm1,
  poly.adm2,
  varname1,
  varname2
)

Arguments

Value

a list of two data frames for admin 1 and admin 2 urban ratios

Examples

## 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)

Function to obtain subnational estimates from DHS API

Description

Function to obtain subnational estimates from DHS API

Usage

get_api_table(country, survey, indicator, simplify = TRUE)

Arguments

Value

a data frame of the DHS indicator estimates

Examples

## 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)

HA_HIVP_W_HIV hv_hiv_pos "HIV positive test result"

Description

HA_HIVP_W_HIV hv_hiv_pos "HIV positive test result"

Usage

hv_hiv_pos(Rdata)

Arguments

Value

A partially processed data.frame that will be used in survryPrev::getDHSindicator. The whole function can be used as a parameter in survryPrev::getDHSindicator

Author(s)

Qianyu Dong

Examples

## 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)

Get scatter plot for any two model results

Description

This function return scatter plot at admin 1 level for any two model results

Usage

intervalPlot(admin = 0, compare = FALSE, model = NULL, group = FALSE)

Arguments

Value

This function returns the dataset that contain district name and population for given tiff files and polygons of admin level.

Author(s)

Qianyu Dong

Examples

## 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)

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

Description

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

Usage

ml_hhaccess(Rdata)

Arguments

Value

A partially processed data.frame that will be used in survryPrev::getDHSindicator. The whole function can be used as a parameter in survryPrev::getDHSindicator

Author(s)

Qianyu Dong

Examples

## 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)

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

Description

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

Usage

nt_ch_any_anem(Rdata)

Arguments

Value

A partially processed data.frame that will be used in survryPrev::getDHSindicator. The whole function can be used as a parameter in survryPrev::getDHSindicator

Author(s)

Qianyu Dong

Examples

## 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).

Description

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).

Usage

nt_ch_stunt(Rdata)

Arguments

Value

A partially processed data.frame that will be used in survryPrev::getDHSindicator. The whole function can be used as a parameter in survryPrev::getDHSindicator

Author(s)

Qianyu Dong

Examples

## 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.

Description

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.

Usage

nt_ch_wast(Rdata)

Arguments

Value

A partially processed data.frame that will be used in survryPrev::getDHSindicator. The whole function can be used as a parameter in survryPrev::getDHSindicator

Author(s)

Qianyu Dong

Examples

## 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)

Description

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)

Usage

nt_ebf(Rdata)

Arguments

Value

A partially processed data.frame that will be used in survryPrev::getDHSindicator. The whole function can be used as a parameter in survryPrev::getDHSindicator

Author(s)

Qianyu Dong

Examples

## 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

Description

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

Usage

nt_wm_any_anem(Rdata)

Arguments

Value

A partially processed data.frame that will be used in survryPrev::getDHSindicator. The whole function can be used as a parameter in survryPrev::getDHSindicator

Author(s)

Qianyu Dong

Examples

## 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)

Description

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)

Usage

nt_wm_thin(Rdata)

Arguments

Value

A partially processed data.frame that will be used in survryPrev::getDHSindicator. The whole function can be used as a parameter in survryPrev::getDHSindicator

Author(s)

Qianyu Dong

Examples

## 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"

Description

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"

Usage

ph_sani_basic(Rdata)

Arguments

Value

A partially processed data.frame that will be used in survryPrev::getDHSindicator. The whole function can be used as a parameter in survryPrev::getDHSindicator

Author(s)

Qianyu Dong

Examples

## 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

Description

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

Usage

ph_sani_improve(Rdata)

Arguments

Value

A partially processed data.frame that will be used in survryPrev::getDHSindicator. The whole function can be used as a parameter in survryPrev::getDHSindicator

Author(s)

Qianyu Dong

Examples

## 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)

RH_ANCN_W_N4P ancvisit4+ RH_ANCN_W_N4P IR Antenatal visits for pregnancy: 4+ visits

Description

RH_ANCN_W_N4P ancvisit4+ RH_ANCN_W_N4P IR Antenatal visits for pregnancy: 4+ visits

Usage

rh_anc_4vs(Rdata)

Arguments

Value

A partially processed data.frame that will be used in survryPrev::getDHSindicator. The whole function can be used as a parameter in survryPrev::getDHSindicator

Author(s)

Qianyu Dong

Examples

## 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)

RH_DELA_C_SKP IR or BR Assistance during delivery from a skilled provider

Description

RH_DELA_C_SKP IR or BR Assistance during delivery from a skilled provider

Usage

rh_del_pvskill(Rdata)

Arguments

Value

A partially processed data.frame that will be used in survryPrev::getDHSindicator. The whole function can be used as a parameter in survryPrev::getDHSindicator

Author(s)

Qianyu Dong

Examples

## 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)

Get scatter plot for any two model results

Description

This function return scatter plot at admin 1 level for any two model results

Usage

scatterPlot(
  res1,
  value1,
  res2,
  value2,
  label1,
  label2,
  by.res1,
  by.res2,
  title
)

Arguments

Value

This function returns the dataset that contain district name and population for given tiff files and polygons of admin level

Author(s)

Qianyu Dong

Examples

## 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)

Table of built-in indicators.

Description

A data frame of indicators currently implemented in the package

Usage

data(surveyPrevIndicators)

Format

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

Description

WS_SRCE_P_BAS Population using a basic water source PH_WATER.do ph_wtr_basic "Basic water service" PR

Usage

watersource_adj(Rdata)

Arguments

Value

A partially processed data.frame that will be used in survryPrev::getDHSindicator. The whole function can be used as a parameter in survryPrev::getDHSindicator

Author(s)

Qianyu Dong

Examples

## 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)