lavaan_dmacs: Summary of measurement nonequivalence effects

In ddueber/dmacs: Measurement Nonequivalence Effect Size Calculator

Summary of measurement nonequivalence effects

Description

lavaan_dmacs returns a summary of measurement non-equivalence effects given a fitted multigroup lavaan object.

Usage

lavaan_dmacs(fit, RefGroup = 1, dtype = "pooled", MEtype = "Group")

Arguments

fit	is a fitted lavaan multi-group object. Only CFA models are supported, and be sure to have an anchor item.
RefGroup	can be the name of the reference group (as a string), or the index of the reference group (as a number). RefGroup defaults to the first group if no value is provided. It is strongly recommended to provide the reference group as a string, since group names in data are often ordered by their appearance in the data, not alphabetically. When long = TRUE, RefGroup is either the index of the reference timepoint or the name of the latent factor at the reference timepoint.
dtype	describes the pooling of standard deviations for use in the denominator of the dmacs effect size. Possibilities are "pooled" for pooled standard deviations, or "glass" for always using the standard deviation of the reference group.
MEtype	described the type of measurement equivalence testing being performed. Defaults to "Group" for multigroup testing. Other option is "Longitudinal" (or "Long") for longitudinal testing. Only unidimensional models are supported with longitudinal data. Note that output will always use indicator names from the reference timepoint.

Value

A list, indexed by group or timepoint, of lists of measurement nonequivalence effects from Nye and Drasgow (2011), including dmacs, expected bias in the mean score by item, expected bias in the mean total score, and expected bias in the variance of the total score. Expected bias in the variance of the total score is only supplied for unidimensional models in the current version of this package

References

Nye, C. & Drasgow, F. (2011). Effect size indices for analyses of measurement equivalence: Understanding the practical importance of differences between groups. Journal of Applied Psychology, 96(5), 966-980.

Examples

HS.model <- '  visual  =~ x1 + x2 + x3
               textual =~ x4 + x5 + x6
               speed   =~ x7 + x8 + x9 '
fit <- lavaan::cfa(HS.model,
                  data = lavaan::HolzingerSwineford1939,
                  group = "school")
lavaan_dmacs(fit, RefGroup = "Pasteur")

ddueber/dmacs documentation built on Feb. 8, 2023, 11:31 p.m.