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Equalize Paired Item Response Levels

Source: R/equalize_levels.R
equalize_levels.Rd

equalize_levels() prepares paired Time 1 and Time 2 PROM items for longitudinal CFA by ensuring that each item has the same observed response levels at both time points. Sparse or mismatched response categories are collapsed consistently within each item pair.

Usage

equalize_levels(
  data,
  pair_by = c("position", "suffix"),
  t1_suffix = NULL,
  t2_suffix = NULL,
  min_resp = 5L,
  verbose = TRUE,
  print_tables = TRUE
)

Arguments

data

A data frame containing paired item variables. Do not include the transition rating variable.

pair_by

Pairing method. "position" assumes the first half of columns are Time 1 items and the second half are Time 2 items. "suffix" detects item pairs using t1_suffix and t2_suffix.

t1_suffix

Regex suffix identifying Time 1 items when pair_by = "suffix". Use "" when Time 1 items have no suffix.

t2_suffix

Regex suffix identifying Time 2 items when pair_by = "suffix".

min_resp

Integer. Minimum number of responses required in each response category at both time points. Categories with fewer responses are collapsed.

verbose

Logical. If TRUE, prints progress messages.

print_tables

Logical. If TRUE, prints before/after frequency tables only for item pairs that required collapsing or equalization.

Value

A list with components:

data

The processed data frame, ordered as T1 items followed by T2 items.

pair_map

A data frame describing matched T1/T2 item pairs.

collapsed_items

A data frame listing item pairs that required collapsing/equalization.

before_tables

Frequency tables before collapsing for affected item pairs.

after_tables

Frequency tables after collapsing for affected item pairs.

mappings

Category mappings for affected item pairs.

summary

A data frame summarizing all item pairs.

Details

Item pairs can be detected either by column position or by suffix patterns. The function does not shift or rescale item scores; it only collapses and equalizes response levels within paired items.

Examples

dat <- data.frame(
  item1 = c(1, 1, 2, 2, 3, 3, 3, 4),
  item2 = c(1, 2, 2, 3, 3, 3, 4, 4),
  item1.1 = c(1, 2, 2, 2, 3, 4, 4, 4),
  item2.1 = c(1, 1, 2, 2, 3, 4, 4, 4)
)

out <- equalize_levels(
  data = dat,
  pair_by = "suffix",
  t1_suffix = "",
  t2_suffix = "\\.1",
  min_resp = 2,
  verbose = FALSE,
  print_tables = FALSE
)