denominator_sensitivity: Denominator-sensitivity profile across six symmetric...

In ltgsmd: Latent True-Score and Target-Population Anchored Geometric SMD

Denominator-sensitivity profile across six symmetric denominators

Description

Computes the LTG-SMD estimate under each of six symmetric denominator rules applied to the group-specific reference-sample true-score standard deviations: geometric (default), arithmetic, harmonic, root mean square, minimum, and maximum. This profile mirrors the six symmetric denominators compared in Simulation D (Section 5.3 of the companion paper; Supplementary Section D.4) and is recommended as supplementary material (Supplementary Section F.2.4), particularly when group-specific reference true-score variances differ markedly.

Usage

denominator_sensitivity(x)

Arguments

x	An "ltg_smd" object.

Value

A data frame with one row per denominator rule, columns denominator, D, estimate. Class "denominator_sensitivity".

Examples

set.seed(2026)
gen_items <- function(n, shift = 0) {
  true <- rnorm(n)
  data.frame(
    item1 = true + rnorm(n, sd = 0.6) + shift,
    item2 = true + rnorm(n, sd = 0.6) + shift,
    item3 = true + rnorm(n, sd = 0.6) + shift,
    item4 = true + rnorm(n, sd = 0.6) + shift
  )
}
study_df <- rbind(
  cbind(condition = "control",   gen_items(15)),
  cbind(condition = "treatment", gen_items(15, shift = 0.5))
)
reference_df <- rbind(
  cbind(condition = "control",   gen_items(30)),
  cbind(condition = "treatment", gen_items(30, shift = 0.5))
)
result <- compute_ltg_smd(study_df, reference_df,
  group_var = "condition", items = c("item1", "item2", "item3", "item4"),
  group_levels = c(reference = "control", focal = "treatment"))
sens <- denominator_sensitivity(result)
print(sens)

ltgsmd documentation built on Sept. 27, 2026, 5:07 p.m.