Compare Model Fit of Nested Dyadic Invariance Models

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,
  parsimonyFirst = FALSE,
  gtTab = FALSE,
  writeTo = NULL,
  fileName = NULL
)

Arguments

mods: A list of nested lavaan dyadic invariance models, in the order of residual, intercept, loading, configural
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 table(s) in gt::gt() table object format (TRUE). By default (FALSE), the table(s) are generated in tibble::tibble() format. Users can also apply the writeTo argument if they wish to export the gt::gt() table object(s).
writeTo: A character string specifying a directory path to where the output file(s) should be saved. If set to ".", the file(s) will be written to the current working directory. The default is NULL, and examples use a temporary directory created by tempdir(). When dealing with tabular output, writeTo is only relevant if gtTab = TRUE.
fileName: A character string specifying a desired base name for the output file. The default is NULL. The specified name will be automatically appended with the appropriate file extension (e.g., .txt for lavaan scripts, .rtf for tabular output when gtTab = TRUE, or other extensions as appropriate for the output type). 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

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.

Examples


dvn <- scrapeVarCross(
  dat = commitmentQ, x_order = "spi",
  x_stem = "sat.g", x_delim1 = ".", x_delim2 = "_", distinguish_1 = "1", distinguish_2 = "2"
)
#> 
#> ── Variable Scraping Summary ──
#> 
#> ✔ Successfully scraped 1 latent variable: sat.g
#> ℹ sat.g: 5 indicators for P1 (1), 5 indicators for P2 (2)
#> ℹ Total indicators: 10

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"
)
#> Output stored in: /tmp/RtmpIVCISQ/dCFA_Invar_Standard.rtf


  mod
      chisq
      df
      pvalue
      aic
      bic
      rmsea
      cfi
      chisq_diff
      df_diff
      p_diff
      aic_diff
      bic_diff
      rmsea_diff
      cfi_diff
    
configural
78.842
42
0.000
3855.175
3918.308
0.087
0.970
NA
NA
NA
NA
NA
NA
NA
loading
60.321
37
0.009
3846.654
3923.512
0.074
0.981
-18.521
-5
0.002
-8.521
5.204
-0.013
0.011
intercept
58.810
33
0.004
3853.143
3940.981
0.082
0.979
-1.511
-4
0.825
6.489
17.469
0.008
-0.002
residual
53.026
29
0.004
3855.359
3954.176
0.085
0.981
-5.784
-4
0.216
2.216
13.196
0.002
0.001

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"
)
#> Output stored in: /tmp/RtmpIVCISQ/dCFA_Invar_Reverse.rtf


  mod
      chisq
      df
      pvalue
      aic
      bic
      rmsea
      cfi
      chisq_diff
      df_diff
      p_diff
      aic_diff
      bic_diff
      rmsea_diff
      cfi_diff
    
residual
53.026
29
0.004
3855.359
3954.176
0.085
0.981
NA
NA
NA
NA
NA
NA
NA
intercept
58.810
33
0.004
3853.143
3940.981
0.082
0.979
5.784
4
0.216
-2.216
-13.196
-0.002
-0.001
loading
60.321
37
0.009
3846.654
3923.512
0.074
0.981
1.511
4
0.825
-6.489
-17.469
-0.008
0.002
configural
78.842
42
0.000
3855.175
3918.308
0.087
0.970
18.521
5
0.002
8.521
-5.204
0.013
-0.011

mod	chisq	df	pvalue	aic	bic	rmsea	cfi	chisq_diff	df_diff	p_diff	aic_diff	bic_diff	rmsea_diff	cfi_diff
configural	78.842	42	0.000	3855.175	3918.308	0.087	0.970	NA	NA	NA	NA	NA	NA	NA
loading	60.321	37	0.009	3846.654	3923.512	0.074	0.981	-18.521	-5	0.002	-8.521	5.204	-0.013	0.011
intercept	58.810	33	0.004	3853.143	3940.981	0.082	0.979	-1.511	-4	0.825	6.489	17.469	0.008	-0.002
residual	53.026	29	0.004	3855.359	3954.176	0.085	0.981	-5.784	-4	0.216	2.216	13.196	0.002	0.001