Skip to contents

A Function That Fits and Compares Competing Dyadic Uni-construct Models

Source: R/outputUniConstructComp.R
outputUniConstructComp.Rd

This function takes the outputted object from scrapeVarCross() along with the corresponding dataset and automatically tests competing uni-construct dyadic models for the latent variable under consideration. It inspects four possible model variants:

Usage

outputUniConstructComp(
  dvn,
  dat,
  indexes = c("df", "chisq", "cfi", "rmsea", "bic", "GenTEFI"),
  ...,
  gtTab = FALSE,
  writeTo = NULL,
  fileName = NULL
)

Arguments

dvn

Input dvn list from scrapeVarCross().

dat

Input data frame containing the dataset for model estimation.

indexes

Input character vector specifying which index(es) to return. Default is c("df", "chisq", "cfi", "rmsea", "bic", "GenTEFI"). Note:

  • Valid entries include "GenTEFI"—the Generalized Total Entropy Fit Index (see Golino et al., 2024)—and those from lavaan::fitMeasures().

  • If "chisq" is entered, chi-squared difference tests are automatically performed via lavaan::lavTestLRT(), and the resulting p-values are added to the output.

...

Additional arguments to be passed to lavaan::cfa(), allowing users to customize model estimation settings. By default, the models are fit with maximum-likelihood estimation (estimator = "ml") and missing data are handled via listwise deletion (missing = "listwise"), as per lavaan::cfa()'s default behaviour.

gtTab

A logical input indicating whether to generate the requested index(es) for each fitted model (requested via the indexes argument) in gt::gt() table object format (TRUE). Users can also apply the writeTo argument if they wish to export the gt::gt() table object.

writeTo

A character vector 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. The resulting base name will automatically be appended with a .rtf file extension. fileName is only relevant if gtTab = TRUE and writeTo is specified.

Value

A list containing up to two components:

  • Indexes: A tibble::tibble() if gtTab = FALSE (default), or gt::gt() object if gtTab = TRUE, with the desired index(es) for each fitted model (requested via the indexes argument).

  • GenTEFI: A tibble::tibble() of the GenTEFI (if "GenTEFI" is included in the indexes argument).

Details

  • If "chisq" is included in indexes, the specific form of the applied chi-squared difference test (e.g., standard vs. robust) is determined automatically by lavaan::lavTestLRT(), based on the model estimation method used.

  • 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(
  commitmentQ,
  x_order = "spi",
  x_stem = "sat.g",
  x_delim1 = ".",
  x_delim2="_",
  distinguish_1="1",
  distinguish_2="2"
  )
  
  outputUniConstructComp(
  dvn,
  commitmentQ,
  missing = "fiml"
  )
#> According to GenTEFI (-15.173), 
#>           higher-order models (e.g., bifactor or hierarchical) fit the data better than lower-order models (e.g., correlated factors),
#>           as the higher-order TEFI (-9.419) is smaller than the lower-order TEFI (-5.754).
#> $Indexes
#> # A tibble: 4 × 14
#>   Model          Type  genTEFI    df chisq   cfi  rmsea   bic df_diff chisq_diff
#>   <chr>          <chr> <chr>   <dbl> <dbl> <dbl>  <dbl> <dbl>   <dbl>      <dbl>
#> 1 Bifactor       High… Yes        20  41.3 0.983 0.0951 4077.      NA      NA   
#> 2 Hierarchical   High… Yes        29  49.1 0.984 0.0767 4042.       9       7.78
#> 3 Correlated Fa… Lowe… No         29  49.1 0.984 0.0767 4042.      NA      NA   
#> 4 Unidimensional Lowe… No         30 235.  0.839 0.240  4223.       1     186.  
#> # ℹ 4 more variables: chisq_diff_test_p <dbl>, cfi_diff <dbl>,
#> #   rmsea_diff <dbl>, bic_diff <dbl>
#> 
#> $`GenTEFI Details`
#> # A tibble: 1 × 3
#>   VN.Entropy.Fit Lower.Order.VN Higher.Order.VN
#>            <dbl>          <dbl>           <dbl>
#> 1          -15.2          -5.75           -9.42
#> 
  
  outputUniConstructComp(
  dvn,
  commitmentQ,
  indexes = c("df", "bic"),
  missing = "fiml"
  )
#> # A tibble: 4 × 6
#>   Model              Type            df   bic df_diff bic_diff
#>   <chr>              <chr>        <dbl> <dbl>   <dbl>    <dbl>
#> 1 Bifactor           Higher Order    20 4077.      NA     NA  
#> 2 Hierarchical       Higher Order    29 4042.       9    -35.2
#> 3 Correlated Factors Lower Order     29 4042.      NA     NA  
#> 4 Unidimensional     Lower Order     30 4223.       1    181. 
  
  outputUniConstructComp(
  dvn,
  commitmentQ,
  indexes = c("df", "bic"),
  estimator = "ml",
  missing = "fiml"
  )
#> # A tibble: 4 × 6
#>   Model              Type            df   bic df_diff bic_diff
#>   <chr>              <chr>        <dbl> <dbl>   <dbl>    <dbl>
#> 1 Bifactor           Higher Order    20 4077.      NA     NA  
#> 2 Hierarchical       Higher Order    29 4042.       9    -35.2
#> 3 Correlated Factors Lower Order     29 4042.      NA     NA  
#> 4 Unidimensional     Lower Order     30 4223.       1    181. 
  
  outputUniConstructComp(
  dvn,
  commitmentQ,
  indexes = c("df", "bic"),
  missing = "fiml",
  gtTab = TRUE,
  writeTo = tempdir(),
  fileName = "uni-construct-dyad-models"
  )
#> Output stored in: /tmp/RtmpmQWsXV/uni-construct-dyad-models.rtf



  
Model
      Type
      df
      bic
      df_diff
      bic_diff
    
Bifactor
Higher Order
20
4077.220
NA
NA
Hierarchical
Higher Order
29
4042.068
9
-35.1525
Correlated Factors
Lower Order
29
4042.068
NA
NA
Unidimensional
Lower Order
30
4222.850
1
180.7826