outputInvarCompTab: Compare Model Fit of Nested Dyadic Invariance Models

In dySEM: Dyadic Structural Equation Modeling

Compare Model Fit of Nested Dyadic Invariance Models

Description

outputInvarCompTab() is used to compare the model fit of nested dyadic invariance models in order from most parsimonious (residual) to least parsimonious (configural)

Usage

outputInvarCompTab(mods, gtTab = FALSE, writeTo = NULL, fileName = NULL)

Arguments

mods	A list of nested lavaan dyadic invariance models, in the order of residual, intercept, loading, configural
gtTab	A logical input indicating whether to generate the output in gt::gt() table object format (TRUE). By default (FALSE), the output is generated in tibble::tibble() format. Users can also apply the writeTo argument if they wish to export the gt:gt() table object.
writeTo	A character string specifying a directory path to where the gt::gt() table object should be saved. If set to ".", the file will be written to the current working directory. The default is NULL, and examples use a temporary directory created by tempdir(). writeTo is only relevant if gtTab = TRUE.
fileName	A character string specifying a desired base name for the output gt::gt() file. If a fileName is not provided (i.e., fileName = NULL), then a default will be used (i.e., "dySEM_table"). The resulting base name will automatically be appended with a .rtf file extension. fileName is only relevant if gtTab = TRUE and writeTo is specified.

Details

• If gtTab = TRUE and writeTo is specified, then output will simultaneously be saved as a .rtf file to the user's specified directory.

• If output file is successfully saved, a confirmation message will be printed to the console.

• If a file with the same name already exists in the user's chosen directory, it will be overwritten.

Value

A tibble::tibble() if gtTab = FALSE (default), or gt::gt() object if gtTab = TRUE, of model fit statistics for each model, as well as the difference in fit statistics between each model and the previous model

Examples

dvn <- scrapeVarCross(dat = commitmentQ, x_order = "spi",
x_stem = "sat.g", x_delim1 = ".", x_delim2="_", distinguish_1="1", distinguish_2="2")

sat.residual.script <- scriptCFA(dvn, lvname = "Sat",
constr_dy_meas = c("loadings", "intercepts", "residuals"), constr_dy_struct = "none")

sat.intercept.script <- scriptCFA(dvn, lvname = "Sat",
constr_dy_meas = c("loadings", "intercepts"), constr_dy_struct = "none")

sat.loading.script <- scriptCFA(dvn, lvname = "Sat",
constr_dy_meas = c("loadings"), constr_dy_struct = "none")

sat.config.script <- scriptCFA(dvn, lvname = "Sat",
constr_dy_meas = "none", constr_dy_struct = "none")

sat.residual.fit <- lavaan::cfa(sat.residual.script, data = commitmentQ,
std.lv = FALSE, auto.fix.first= FALSE, meanstructure = TRUE)

sat.intercept.fit <- lavaan::cfa(sat.intercept.script, data = commitmentQ,
std.lv = FALSE, auto.fix.first= FALSE, meanstructure = TRUE)

sat.loading.fit <- lavaan::cfa(sat.loading.script, data = commitmentQ,
std.lv = FALSE, auto.fix.first= FALSE, meanstructure = TRUE)

sat.config.fit <- lavaan::cfa(sat.config.script, data = commitmentQ,
std.lv = FALSE, auto.fix.first= FALSE, meanstructure = TRUE)

mods <- list(sat.residual.fit, sat.intercept.fit, sat.loading.fit, sat.config.fit)

outputInvarCompTab(mods,
gtTab = TRUE, writeTo = tempdir(), fileName = "dCFA_Invar")

dySEM documentation built on April 4, 2025, 12:47 a.m.