Summary of model object

Transforms coefficients into a standardized factor loading's metric. For MixedClass objects, the fixed and random coefficients are printed. Note that while the output to the console is rounded to three digits, the returned list of objects is not. For simulations, use output <- summary(mod, verbose = FALSE) to suppress the console messages.

# S4 method for SingleGroupClass
summary(
  object,
  rotate = "oblimin",
  Target = NULL,
  suppress = 0,
  suppress.cor = 0,
  verbose = TRUE,
  ...
)

Arguments

object

an object of class SingleGroupClass, MultipleGroupClass, or MixedClass

rotate

a string indicating which rotation to use for exploratory models, primarily from the GPArotation package (see documentation therein).

Rotations currently supported are: 'promax', 'oblimin', 'varimax', 'quartimin', 'targetT', 'targetQ', 'pstT', 'pstQ', 'oblimax', 'entropy', 'quartimax', 'simplimax', 'bentlerT', 'bentlerQ', 'tandemI', 'tandemII', 'geominT', 'geominQ', 'cfT', 'cfQ', 'infomaxT', 'infomaxQ', 'mccammon', 'bifactorT', 'bifactorQ'.

For models that are not exploratory this input will automatically be set to 'none'

Target

a dummy variable matrix indicting a target rotation pattern. This is required for rotations such as 'targetT', 'targetQ', 'pstT', and 'pstQ'

suppress

a numeric value indicating which (possibly rotated) factor loadings should be suppressed. Typical values are around .3 in most statistical software. Default is 0 for no suppression

suppress.cor

same as suppress, but for the correlation matrix output

verbose

logical; allow information to be printed to the console?

...

additional arguments to be passed

References

Chalmers, R., P. (2012). mirt: A Multidimensional Item Response Theory Package for the R Environment. Journal of Statistical Software, 48(6), 1-29. doi:10.18637/jss.v048.i06

See also

coef-method

Examples

# \donttest{
x <- mirt(Science, 2)
summary(x)
#> 
#> Rotation:  oblimin 
#> 
#> Rotated factor loadings: 
#> 
#>              F1      F2    h2
#> Comfort  0.6016  0.0312 0.382
#> Work    -0.0573  0.7971 0.592
#> Future   0.3302  0.5153 0.548
#> Benefit  0.7231 -0.0239 0.506
#> 
#> Rotated SS loadings:  0.997 0.902 
#> 
#> Factor correlations: 
#> 
#>       F1 F2
#> F1 1.000   
#> F2 0.511  1
summary(x, rotate = 'varimax')
#> 
#> Rotation:  varimax 
#> 
#> Rotated factor loadings: 
#> 
#>            F1    F2    h2
#> Comfort 0.579 0.216 0.382
#> Work    0.121 0.760 0.592
#> Future  0.428 0.605 0.548
#> Benefit 0.683 0.200 0.506
#> 
#> Rotated SS loadings:  0.999 1.03 
#> 
#> Factor correlations: 
#> 
#>    F1 F2
#> F1  1   
#> F2  0  1

# }