recommend_dv: Obtain recommendations for discriminant validity testing

In FCO: Flexible Cutoffs for Model Fit Evaluation in Covariance-Based Structural Models

Obtain recommendations for discriminant validity testing

Description

This function recommends on potential issues for discriminant validity testing, based on differences between fit values and differences between flexible cutoffs. Two approaches of testing are supported: merging and constraining.

Usage

recommend_dv(fits, index = "CFI", digits = 3)

Arguments

fits	A list of simulated fit indices obtained from gen_fit. Based on the structure of fits, the number of models is derived.
index	A vector of fit indices or measures provided by function fitmeasures in package lavaan. The default is set to CFI.
digits	An optional integer to round fit values and cutoffs (min: 1, max: 5).

Value

A list of information regarding discriminant validity testing.

Examples

#Note: Demonstration only! Please use higher numbers of replications for your applications (>= 500).
mod <- "
F1 =~ Q5 + Q7 + Q8
F2 =~ Q2 + Q4
F3 =~ Q10 + Q11 + Q12 + Q13 + Q18 + Q19 + Q20 + Q21 + Q22
F4 =~ Q1 + Q17
F5 =~ Q6 + Q14 + Q15 + Q16
"
#Two models for discriminant validity testing, this resembles constraining with a cutoff of .9
fits.dv.con <- gen_fit(
 mod1 = mod,
 x = bb1992,
 rep = 10,
 dv = TRUE,
 dv.factors = c("F4", "F5"),
 dv.cutoff = .9
)
recommend_dv(fits.dv.con)
#Two models for discriminant validity testing, this resembles merging.
fits.dv.merge <- gen_fit(
 mod1 = mod,
 x = bb1992,
 rep = 10,
 dv = TRUE,
 dv.factors = c("F4", "F5"),
 merge.mod = TRUE
)
recommend_dv(fits.dv.merge)

FCO documentation built on March 31, 2023, 7:01 p.m.