rescale_optimism_4: Rescale 4-level optimism questions

In antaldaniel/surveyreader: Data cleaning and integration for survey files

Description

Rescale Eurobarometer trust in institutions variable with two levels, "Very optimistic" and "Fairly optimistic" and "Fairly pessimistic", "Very pessimistic". This is a wrapper function around the rescale_categories function.

Usage

rescale_optimism_4(column, from = c("Very optimistic", "Fairly optimistic",
  "Fairly pessimistic", "Very pessimistic"), to = c(2, 1, -1, -2),
  na_labels = "default", underscore = TRUE, exact_from = TRUE,
  return_class = "numeric")

Arguments

column	A column from a survey data frame where trust in an institution is recorded.
from	Defaults "Very optimistic", "Fairly optimistic" and "Fairly pessimistic", "Very pessimistic".
to	Defaults to c(2,1,-1,-2). If return_class = "character" or return_class = "factor" is selected it returns the abbreviated category names c("very_optimistic", "fairly_optimistic", "fairly_pessimistic", "very_pessimistic").
na_labels	Defaults to "default".
underscore	Defaults to TRUE in which case factor names or character strings contain underscore_between_words. This is a better approach for further programming, but you can choose FALSE for nicer printing results. See examples.
exact_from	Deafults to TRUE. If FALSE you can use the partial matching, but beware that in this case, "twenty" will be replaced by
return_class	Default is "numeric", alternatives "character" or "factor".

Examples

rescale_optimism_4  (column =
c("Very optimistic",
  "Fairly optimistic",
  "Fairly pessimistic",
  "Very pessimistic",
  "DK", "NT/NV"),
na_labels = "default",
return_class = "character")

rescale_optimism_4  (column =
                     c("Very optimistic",
                     "Fairly optimistic",
                     "Fairly pessimistic",
                     "Very pessimistic",
                     "DK", "NT/NV"),
                     na_labels = "default",
                     return_class = "numeric")

antaldaniel/surveyreader documentation built on May 16, 2019, 2:29 a.m.