epikit (version 0.1.6)

add_weights_strata: Add a column of stratified survey weights to a data frame. For use in surveys where you took a sample population out of a larger source population, with a simple-random or stratified survey design.

Description

Creates weight based on dividing stratified population counts from the source population by surveyed counts in the sample population.

Usage

add_weights_strata(
  x,
  p,
  ...,
  population = population,
  surv_weight = "surv_weight",
  surv_weight_ID = "surv_weight_ID"
)

Arguments

x

a data frame of survey data

p

a data frame containing population data for groups in ...

...

shared grouping columns across both x and p. These are used to match the weights to the correct subset of the population.

population

the column in p that defines the population numbers

surv_weight

the name of the new column to store the weights. Defaults to "surv_weight".

surv_weight_ID

the name of the new ID column to be created. Defaults to "surv_weight_ID"

Author

Zhian N. Kamvar Alex Spina Lukas Richter

Examples

# define a fake dataset of survey data
# including household and individual information
x <- data.frame(stringsAsFactors=FALSE,
         cluster = c("Village A", "Village A", "Village A", "Village A",
                     "Village A", "Village B", "Village B", "Village B"),
    household_id = c(1, 1, 1, 1, 2, 2, 2, 2),
     eligibile_n = c(6, 6, 6, 6, 6, 3, 3, 3),
      surveyed_n = c(4, 4, 4, 4, 4, 3, 3, 3),
   individual_id = c(1, 2, 3, 4, 4, 1, 2, 3),
         age_grp = c("0-10", "20-30", "30-40", "50-60", "50-60", "20-30",
                     "50-60", "30-40"),
             sex = c("Male", "Female", "Male", "Female", "Female", "Male",
                     "Female", "Female"),
         outcome = c("Y", "Y", "N", "N", "N", "N", "N", "Y")
)

# define a fake population data set
# including age group, sex, counts and proportions
p <- epikit::gen_population(total = 10000,
  groups = c("0-10", "10-20", "20-30", "30-40", "40-50", "50-60"),
  proportions = c(0.1, 0.2, 0.3, 0.4, 0.2, 0.1))

  # make sure col names match survey dataset
p <- dplyr::rename(p, age_grp = groups, sex = strata, population = n)

# add weights to a stratified simple random sample
# weight based on age group and sex
add_weights_strata(x, p = p, age_grp, sex, population = population)