sub_nonanswers: Remove non-answers and rescale percentage values

In CT-Data-Haven/cwi: Prep for DataHaven's Community Wellbeing Index

Remove non-answers and rescale percentage values

Description

This is a convenience function for removing what might be considered non-answers ("don't know", "refused", etc.) and rescaling the remaining values to add to 1.0.

Usage

sub_nonanswers(
  data,
  response = response,
  value = value,
  nons = c("Don't know", "Refused"),
  factor_response = TRUE,
  rescale = FALSE
)

Arguments

data	A data frame
response	Bare column name of where responses are found, including those considered to be non-answers. Default: response
value	Bare column name of values, Default: value
nons	Character vector of responses to be removed. Default: c("Don't know", "Refused")
factor_response	Logical: if TRUE (default), returns response variable as a factor. This is likely a more useful way to handle response categories once non-answers have been removed.
rescale	Logical: if TRUE, values will be scaled based on their total. If FALSE (the default), values are scaled based on an assumption that all responses add to 1. In some cases, crosstabs with heavy rounding might not add up to 1 when they should, so rescaling helps handle that.

Value

A data frame with the same number of columns as the original, but fewer rows

Examples

if (interactive()) {
xt <- system.file("extdata/test_xtab2018.xlsx", package = "cwi")
df <- read_xtabs(xt, process = TRUE) |>
  dplyr::filter(code == "Q1") |>
  sub_nonanswers()
}

CT-Data-Haven/cwi documentation built on July 1, 2024, 7:45 a.m.