Skip to contents

Stratified Estimate of Average Ranks

Source: R/stratified_avg.R
stratified_avg.Rd

This function estimates the average ranks based on stratification.

Usage

stratified_avg(
  data,
  var_stratum,
  J = NULL,
  main_q,
  anc_correct = NULL,
  labels = NULL,
  seed = 1234,
  weight = NULL,
  n_bootstrap = 200,
  ipw = FALSE,
  verbose = FALSE,
  p_random = NULL
)

Arguments

data

A data frame containing the ranking data as well as the stratifying variable.

var_stratum

The name of the stratifying variable.

J

The number of items in the ranking question. Defaults to NULL, in which case it will be inferred from the data.

main_q

Main ranking question specification. This can be a single column name or unquoted symbol such as `app_identity`, in which case the function looks for `app_identity_1`, `app_identity_2`, and so on. You may also supply `main_q` directly as a character vector or unquoted `c(...)` expression of ranking columns.

anc_correct

Optional indicator for passing the anchor question. If `NULL`, `p_random` is used when supplied; otherwise the function defaults to `p_random = 0` and applies no correction.

labels

A vector of labels for the items being ranked. Defaults to NULL.

seed

Seed for set.seed for reproducibility.

weight

Either a numeric vector of weights with length `nrow(data)`, the name of a weight column in `data`, or an unquoted weight column name. Defaults to `NULL`.

n_bootstrap

Number of bootstraps. Defaults to 200.

ipw

Indicator for using inverse probability weighting. Defaults to FALSE, in which case direct bias estimation will be employed.

verbose

Indicator for verbose output. Defaults to FALSE.

p_random

Optional fixed proportion of random/inattentive respondents. When supplied, this overrides `anc_correct` and a message is shown if both are provided.

Value

A data frame with the bootstrap-estimated average ranks.

Examples

identity2 <- identity
identity2$stratum <- rep(c("group1", "group2"), length.out = nrow(identity2))
out <- suppressMessages(stratified_avg(
  identity2,
  var_stratum = "stratum",
  main_q = "app_identity",
  p_random = 0,
  n_bootstrap = 1,
  seed = 123
))
head(out)
#>       mean           item
#> 1 3.052680 app_identity_1
#> 2 2.536044 app_identity_2
#> 3 1.949168 app_identity_3
#> 4 2.462107 app_identity_4