Package 'bbw'

Title: Blocked Weighted Bootstrap
Description: The blocked weighted bootstrap (BBW) is an estimation technique for use with data from two-stage cluster sampled surveys in which either prior weighting (e.g. population-proportional sampling or PPS as used in Standardized Monitoring and Assessment of Relief and Transitions or SMART surveys) or posterior weighting (e.g. as used in rapid assessment method or RAM and simple spatial sampling method or S3M surveys) is implemented. See Cameron et al (2008) <doi:10.1162/rest.90.3.414> for application of bootstrap to cluster samples. See Aaron et al (2016) <doi:10.1371/journal.pone.0163176> and Aaron et al (2016) <doi:10.1371/journal.pone.0162462> for application of the blocked weighted bootstrap to estimate indicators from two-stage cluster sampled surveys.
Authors: Mark Myatt [aut], Ernest Guevarra [aut, cre]
Maintainer: Ernest Guevarra <[email protected]>
License: GPL-3
Version: 0.2.0
Built: 2024-10-17 04:15:45 UTC
Source: https://github.com/rapidsurveys/bbw

Help Index

Blocked Weighted Bootstrap

Description

The blocked weighted bootstrap (BBW) is an estimation technique for use with data from two-stage cluster sampled surveys in which either prior weighting (e.g. population proportional sampling or PPS as used in SMART surveys) or posterior weighting (e.g. as used in RAM and S3M surveys).

Usage

bootBW(x, w, statistic, params, outputColumns, replicates = 400)

Arguments

x

A data frame with primary sampling unit (PSU) in column named psu
w

A data frame with primary sampling unit (PSU) in column named psu and survey weight (i.e. PSU population) in column named pop
statistic

A function operating on data in x (see example)
params

Parameters (named columns in x) passed to the function specified in statistic
outputColumns

Names of columns in output data frame
replicates

Number of bootstrap replicates

Value

A data frame with:

  • ncol = length(outputColumns)

  • nrow = replicates

  • names = outputColumns

Examples

# Example function - estimate a proportion for a binary (0/1) variable):

oneP <- function(x, params) {
  v1 <- params[1]
  v1Data <- x[[v1]]
  oneP <- mean(v1Data, na.rm = TRUE)
  return(oneP)
}

# Example call to bootBW function using RAM-OP test data:

bootP <- bootBW(x = indicatorsHH,
                w = villageData,
                statistic = oneP,
                params = "anc1",
                outputColumns = "anc1",
                replicates = 9)

# Example estimate with 95% CI:

quantile(bootP, probs = c(0.500, 0.025, 0.975), na.rm = TRUE)

Simple proportion statistics function for bootstrap estimation

Description

Simple proportion statistics function for bootstrap estimation

Usage

bootClassic(x, params)

Arguments

x

A data frame with primary sampling unit (PSU) in column named psu and with data column/s containing the binary variable/s (0/1) of interest with column names corresponding to params values
params

A vector of column names corresponding to the binary variables of interest contained in x

Value

A numeric vector of the mean of each binary variable of interest with length equal to length(params)

Examples

# Example call to bootClassic function

meanResults <- bootClassic(x = indicatorsHH,
                           params = "anc1")

PROBIT statistics function for bootstrap estimation

Description

PROBIT statistics function for bootstrap estimation

Usage

bootPROBIT(x, params, threshold = THRESHOLD)

Arguments

x

A data frame with primary sampling unit (PSU) in column named psu and with data column/s containing the continuous variable/s of interest with column names corresponding to params values
params

A vector of column names corresponding to the continuous variables of interest contained in x
threshold

cut-off value for continuous variable to differentiate case and non-case

Value

A numeric vector of the PROBIT estimate of each continuous variable of interest with length equal to length(params)

Examples

# Example call to bootBW function:

bootPROBIT(x = indicatorsCH1,
           params = "muac1",
           threshold = 115)

Child Morbidity, Health Service Coverage, Anthropometry

Description

Child indicators on morbidity, health service coverage and anthropometry calculated from survey data collected in survey conducted in 4 districts from 3 regions in Somalia.

Usage

indicatorsCH1

Format

A data frame with 14 columns and 3090 rows.

Variable Description
psu The PSU identifier. This must use the same coding system used to identify the PSUs that is used in the indicators dataset
mID The mother identifier
cID The child identifier
ch1 Diarrhoea in the past 2 weeks (0/1)
ch2 Fever in the past 2 weeks (0/1)
ch3 Cough in the past 2 weeks (0/1)
ch4 Immunisation card (0/1)
ch5 BCG immunisation (0/1)
ch6 Vitamin A coverage in the past month (0/1)
ch7 Anti-helminth coverage in the past month (0/1)
sex Sex of child
muac1 Mid-upper arm circumference in mm
muac2 Mid-upper arm circumference in mm
oedema Oedema (0/1)

Source

Mother and child health and nutrition survey in 3 regions of Somalia

Examples

indicatorsCH1

Infant and Child Feeding Index

Description

Infant and young child feeding indicators using the infant and child feeding index (ICFI) by Arimond and Ruel. Calculated from survey data collected in survey conducted in 4 districts from 3 regions in Somalia.

Usage

indicatorsCH2

Format

A data frame with 13 columns and 2083 rows.

Variable Description
psu The PSU identifier. This must use the same coding system used to identify the PSUs that is used in the indicators dataset
mID The mother identifier
cID The child identifier
ebf Exclusive breastfeeding (0/1)
cbf Continued breastfeeding (0/1)
ddd Dietary diversity (0/1)
mfd Meal frequency (0/1)
icfi Infant and child feeding index (from 0 to 6)
iycf Good IYCF
icfiProp Good ICFI
age Child's age
bf Child is breastfeeding (0/1)
bfStop Age in months child stopped breastfeeding

Source

Mother and child health and nutrition survey in 3 regions of Somalia

Examples

indicatorsCH2

Mother Indicators Dataset

Description

Mother indicators for health and nutrition calculated from survey data collected in survey conducted in 4 districts from 3 regions in Somalia.

Usage

indicatorsHH

Format

A data frame with 24 columns and 2136 rows:

Variable Description
psu The PSU identifier. This must use the same coding system used to identify the PSUs that is used in the indicators dataset
mID The mother identifier
mMUAC Mothers with mid-upper arm circumference < 230 mm (0/1)
anc1 At least 1 antenatal care visit with a trained health professional (0/1)
anc2 At least 4 antenatal care visits with any service provider (0/1)
anc3 FeFol coverage (0/1)
anc4 Vitamin A coverage (0/1)
wash1 Improved sources of drinking water (0/1)
wash2 Improved sources of other water (0/1)
wash3 Probable safe drinking water (0/1)
wash4 Number of litres of water collected in a day
wash5 Improved toilet facilities (0/1)
wash6 Human waste disposal practices / behaviour (0/1)
wash7a Handwashing score (from 0 to 5)
wash7b Handwashing score of 5 (0/1)
hhs1 Household hunger score (from 0 to 6)
hhs2 Little or no hunger (0/1)
hhs3 Moderate hunger (0/1)
hhs4 Severe hunger (0/1)
mfg Mother's dietary diversity score
pVitA Plant-based vitamin A-rich foods (0/1)
aVitA Animal-based vitamin A-rich foods (0/1)
xVitA Any vitamin A-rich foods (0/1)
iron Iron-rich foods (0/1)

Source

Mother and child health and nutrition survey in 3 regions of Somalia

Examples

indicatorsHH

Recode

Description

Utility function that recodes variables based on user recode specifications. Handles both numeric or factor variables.

Usage

recode(var, recodes, afr, anr = TRUE, levels)

Arguments

var

Variable to recode
recodes

Character string of recode specifications:

  • Recode specifications in a character string separated by semicolons of the form input=output as in: "1=1;2=1;3:6=2;else=NA"

    \item If an input value satisfies more than one specification, then the
first (reading from left to right) is applied

\item If no specification is satisfied, then the input value is carried
over to the result unchanged

\item \code{NA} is allowed on both input and output

\item The following recode specifications are supported:

    \tabular{lll}{
      \strong{Specification} \tab \strong{Example}          \tab \strong{Notes}                                                 \cr
      Single values          \tab \code{9=NA}               \tab                                                                \cr
      Set of values          \tab \code{c(1,2,5)=1}         \tab The left-hand-side is any R function call that returns a vector\cr
                             \tab \code{seq(1,9,2)='odd'}   \tab                                                                \cr
                             \tab \code{1:10=1}             \tab                                                                \cr
      Range of values        \tab \code{7:9=3}              \tab Special values \code{lo} and \code{hi} may be used             \cr
                             \tab \code{lo:115=1}           \tab                                                                \cr
      Other values           \tab \code{else=NA}            \tab
    }

\item Character values are quoted as in :

     \code{recodes = "c(1,2,5)='sanitary' else='unsanitary'"}

\item The output may be the (scalar) result of a function call as in:

     \code{recodes = "999=median(var, na.rm = TRUE)"}

\item Users are advised to carefully check the results of \code{recode()} calls
with any outputs that are the results of a function call.

\item The output may be the (scalar) value of a variable as in:

     \code{recodes = "999=scalarVariable"}

\item If all of the output values are numeric, and if \code{'afr'} is \code{FALSE},
then a numeric result is returned; if \code{var} is a factor then
(by default) so is the result.
afr

Return a factor. Default is TRUE if var is a factor and is FALSE otherwise
anr

Coerce result to numeric (default is TRUE)
levels

Order of the levels in the returned factor; the default is to use the sort order of the level names.

Value

Recoded variable

Examples

# Recode values from 1 to 9 to varios specifications
var <- sample(x = 1:9, size = 100, replace = TRUE)

# Recode single values
recode(var = var, recodes = "9=NA")

# Recode set of values
recode(var = var, recodes = "c(1,2,5)=1")

# Recode range of values
recode(var = var, recodes = "1:3=1;4:6=2;7:9=3")

# Recode other values
recode(var = var, recodes = "c(1,2,5)=1;else=NA")

Cluster Population Weights Dataset

Description

Dataset containing cluster population weights for use in performing posterior weighting with the blocked weighted bootstrap approach. This dataset is from a mother and child health and nutrition survey conducted in 4 districts from 3 regions in Somalia.

Usage

villageData

Format

A data frame with 6 columns and 117 rows:

Variable Description
region Region in Somalia from which the cluster belongs to
district District in Somalia from which the cluster belongs to
psu The PSU identifier. This must use the same coding system used to identify the PSUs that is used in the indicators dataset
lon Longitude coordinate of the cluster
lat Latitude coordinate of the cluster
pop Population size of the cluster

Source

Mother and child health and nutrition survey in 3 regions of Somalia

Examples

villageData