View source: R/outputInvarCompTab.R
outputInvarCompTab | R Documentation |
outputInvarCompTab()
is used to compare the model fit of nested dyadic invariance models
in order from most parsimonious (residual) to least parsimonious (configural)
outputInvarCompTab(
mods,
parsimonyFirst = FALSE,
gtTab = FALSE,
writeTo = NULL,
fileName = NULL
)
mods |
A list of nested |
parsimonyFirst |
A logical input indicating whether to prioritize the residual dyadic invariance (i.e. most parsimonious measurement model) as the baseline model for nested comparisons, or to prioritize the configural dyadic invariance (i.e. least parsimonious measurement model). Defaults to FALSE (i.e., configural dyadic invariance is the baseline model). |
gtTab |
A logical input indicating whether to generate the output in |
writeTo |
A character string specifying a directory path to where the |
fileName |
A character string specifying a desired base name for the output |
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.
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
dvn <- scrapeVarCross(dat = commitmentQ, x_order = "spi",
x_stem = "sat.g", x_delim1 = ".", x_delim2="_", distinguish_1="1", distinguish_2="2")
sat.residual.script <- scriptCor(dvn, lvname = "Sat",
constr_dy_meas = c("loadings", "intercepts", "residuals"), constr_dy_struct = "none")
sat.intercept.script <- scriptCor(dvn, lvname = "Sat",
constr_dy_meas = c("loadings", "intercepts"), constr_dy_struct = "none")
sat.loading.script <- scriptCor(dvn, lvname = "Sat",
constr_dy_meas = c("loadings"), constr_dy_struct = "none")
sat.config.script <- scriptCor(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, parsimonyFirst = FALSE,
gtTab = TRUE, writeTo = tempdir(), fileName = "dCFA_Invar_Standard")
mods <- list(sat.config.fit, sat.loading.fit, sat.intercept.fit, sat.residual.fit)
outputInvarCompTab(mods, parsimonyFirst = TRUE,
gtTab = TRUE, writeTo = tempdir(), fileName = "dCFA_Invar_Reverse")
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