Flag suspicious survey responses via the Response Entropy Index (REI)

This function takes a data frame, optional header information, variables to consider, and a range for a Likert scale. It then calculates the Response Entropy Index (REI) and flags suspicious entries based on percentiles. Note that no rows are removed; entries are only flagged via the Suspicious column.

Usage

remove_outliers_REI(df, header = FALSE, variables = "", range = c(1, 5))

Arguments

df: Data frame containing the data.
header: Logical indicating if the data frame has a header. Defaults to FALSE.
variables: Which variables to consider: either a single character string with names separated by commas ("var1,var2") or a character vector (c("var1", "var2")).
range: Numeric vector of length 2 specifying the range of the Likert scale (used to sanity-check the responses). Defaults to c(1, 5).

Value

A data frame with calculated REI, percentile, and a 'Suspicious' flag.

Details

Missing responses are ignored when tallying answers. Responses outside the declared Likert range trigger a warning (they often indicate mis-coded data) but are still included in the REI computation.

For more information on the REI method, refer to: Response Entropy Index Method

Examples

# \donttest{
df <- data.frame(var1 = c(1, 2, 3), var2 = c(2, 3, 4))
result <- remove_outliers_REI(df, TRUE, "var1,var2", c(1, 5))
# }