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Show More Major Options in an Output of 'lavaan'

Source: R/show_more_options.R
show_more_options.Rd

Display the values of more major options in a model fitted by lavaan::lavaan() or its wrappers (e.g., lavaan::sem or lavaan::cfa()).

Usage

show_more_options(fit)

# S3 method for class 'show_more_options'
print(x, ...)

Arguments

fit

An output of lavaan::lavaan() or its wrappers (e.g., lavaan::cfa() and lavaan::sem())

x

The output of show_more_options().

...

Additional arguments. Ignored.

Value

A show_more_options-class object with a print method that formats the output.

Details

It extracts the values of major options in the output of lavaan::lavaan() or its wrappers (e.g., lavaan::sem or lavaan::cfa(). Most of the values are also reported in the summary of a 'lavaan'-class object. This function is used to show the values in one single table for a quick overview.

It checks the actual values, not the call used. This is useful for understanding how a prepackaged estimator such as ML, MLM, and MLR set other options. It supports the following options:

  • Estimator (estimator)

  • Standard error (se)

  • Model chi-square test(s) (test)

  • Missing data method (missing)

  • Information matrix used for computing standard errors (information)

  • Information matrix used for computing model chi-square (information)

  • Whether the mean structure is included.

It is named show_more_options() to differentiate it from show_options(), originally in the semunpack package, which is intended for new users of lavaan``. The code is adapted from show_options` with more advanced options added.

Methods (by generic)

  • print(show_more_options): The print method of the output of show_more_options().

Author

Shu Fai Cheung https://orcid.org/0000-0002-9871-9448

Examples

library(lavaan)

# From the help page of lavaan::cfa().

HS.model <- '
visual  =~ x1 + x2 + x3
textual =~ x4 + x5 + x6
speed   =~ x7 + x8 + x9
'
fit <- cfa(HS.model, data = HolzingerSwineford1939)

tmp <- show_more_options(fit)
tmp
#>  Options                             Call    Actual  
#>  Estimator(s)                        default ML      
#>  Standard Error (SE)                 default standard
#>  Model Test Statistic(s)             default standard
#>  How Missing Data is Handled         default listwise
#>  Information Matrix (for SE)         default expected
#>  Information Matrix (for Model Test) default expected
#>  Mean Structure                      default No      
#>  'x' Fixed                           default FALSE   

fit <- cfa(HS.model, data = HolzingerSwineford1939, estimator = "MLR")
show_more_options(fit)
#>  Options                             Call    Actual            
#>  Estimator(s)                        MLR     ML                
#>  Standard Error (SE)                 default robust.huber.white
#>  Model Test Statistic(s)             default yuan.bentler.mplus
#>  How Missing Data is Handled         default listwise          
#>  Information Matrix (for SE)         default observed          
#>  Information Matrix (for Model Test) default observed          
#>  Mean Structure                      default No                
#>  'x' Fixed                           default FALSE             
fit <- cfa(HS.model, data = HolzingerSwineford1939, estimator = "MLM")
show_more_options(fit)
#>  Options                             Call    Actual         
#>  Estimator(s)                        MLM     ML             
#>  Standard Error (SE)                 default robust.sem     
#>  Model Test Statistic(s)             default satorra.bentler
#>  How Missing Data is Handled         default listwise       
#>  Information Matrix (for SE)         default expected       
#>  Information Matrix (for Model Test) default expected       
#>  Mean Structure                      default No             
#>  'x' Fixed                           default FALSE