R: A Function for Creating Publication Quality Tables with CFA...

cfa.tab.multi

R Documentation

A Function for Creating Publication Quality Tables with CFA fit indices from several lavaan objects.

Description

Often researchers are required to show fit indices from several CFA models. This function will create publication worthy tables with CFA fit indices from several lavaan class objects. #' To run this function successfully one need to provide at least two lavaan objects. This command supports up-to five lavaan models.

Usage

cfa.tab.multi(x, y, z = NULL, a = NULL, b = NULL, robust = FALSE)

Arguments

`x`	first object of class lavaan (Mandatory).
`y`	second object of class lavaan (Mandatory).
`z`	third object of class lavaan (Optional).
`a`	fourth object of class lavaan (Optional).
`b`	fifth object of class lavaan (Optional).
`robust`	If TRUE, will provide robust fit indices when applicable instead of the default indices.

Value

A summary of CFA fit indices from several lavaan class objects. Output object is a matrix.

Examples

data <- tabledown::FFMQ.CFA
FF.model.Original <- "Observe =~ item1 + item6 + item11 + item15 +
item20 + item26 + item31 + item 36
Describe =~ item2 + item7 + Ritem12 + Ritem16 + Ritem22 + item27 +
item32 + item37
Awareness =~ Ritem5 + Ritem8 + Ritem13 + Ritem18 + Ritem23 + Ritem28 +
Ritem34 + Ritem38
Nonjudge =~ Ritem3 + Ritem10 + Ritem14 + Ritem17 + Ritem25 +
Ritem30+ Ritem35 + Ritem39
Nonreact =~ item4 + item9 + item19 + item21 + item24 + item29 + item33 "
fit.original <- lavaan::cfa(FF.model.Original, data = data,
estimator = "MLR", mimic = "Mplus")
FF.model.Cor <-  "Observe =~ item1 + item6 + item11 + item15 +
item20 + item26 + item31 + item 36
 Describe =~ item2 + item7   + item27 + item32 + item37
Awareness =~ Ritem5 + Ritem8 + Ritem13 + Ritem18 + Ritem23 +
Ritem28 + Ritem34
Nonjudge =~  Ritem10 + Ritem14 + Ritem25 + Ritem30+ Ritem35
 Nonreact =~ item4 + item9 + item19 + item21 + item24 + item29 + item33
Ritem28 ~~ Ritem34
Ritem23 ~~ Ritem34"
fit.Cor <- lavaan::cfa(FF.model.Cor, data = data, estimator = "MLR", mimic = "Mplus")
FF.short <- "Observe =~ item36 + item26 +item20 + item11
Describe =~ item2 + item7 + item27 +  item32
Awareness =~  Ritem8 + Ritem13 + Ritem23 + Ritem28
Nonjudge =~ Ritem10  + Ritem25 + Ritem30 + Ritem35
Nonreact =~ item9 + item19 + item21 + item24"
fit.short <- lavaan::cfa(FF.short, data = data, estimator = "MLR", mimic = "Mplus")
table <- cfa.tab.multi(fit.original, fit.Cor, fit.short, robust = TRUE)