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sirt (version 1.6-0)

lsem.permutationTest: Permutation Test for a Local Structural Equation Model

Description

Performs a permutation test for testing the hypothesis that model parameter are independent of a moderator variable (see Hildebrandt, Wilhelm, & Robitzsch, 2009).

Usage

lsem.permutationTest(lsem.object, B = 1000, residualize = TRUE, verbose = TRUE)

## S3 method for class 'lsem.permutationTest':
summary(object, file=NULL, digits=3, ...)

## S3 method for class 'lsem.permutationTest':
plot(x, type = "global", stattype = "MAD", 
    parindex = NULL, sig_add = TRUE, sig_level = 0.05, sig_pch = 17,  
    sig_lab = "p value", moderator_lab = NULL, digits = 3, title = NULL, 
    parlabels = NULL, ask = TRUE, ...)

Arguments

lsem.object
Fitted object of class lsem with lsem.estimate
B
Number of permutation samples
residualize
Optional logical indicating whether residualization of the moderator should be performed for each permutation sample.
verbose
Optional logical printing information about computation progress.
object
Object of class lsem
file
A file name in which the summary output will be written.
digits
Number of digits.
...
Further arguments to be passed.
x
Object of class lsem
type
Type of the statistic to be plotted. If type="global", a global test will be displayed. If type="pointwise" for each value at the focal point (defined in moderator.grid) are calculated.
stattype
Type of test statistics. Can be MAD (mean absolute deviation), SD (standard deviation) or lin_slo (linear slope).
parindex
Vector of indices of selected parameters.
sig_add
Logical indicating whether significance values (p values) should be displayed.
sig_level
Significance level.
sig_pch
Point symbol for significance value.
sig_lab
Label for significance value (p value).
moderator_lab
Label of the moderator.
title
Title of the plot. Can be a vector.
parlabels
Labels of the parameters. Can be a vector.
ask
A logical which asks for changing the graphic for each parameter.

Value

  • List with following entries
  • teststatData frame with global test statistics. The statistics are SD, MAD and lin_slo with their corresponding p values.
  • parameters_pointwise_testData frame with pointwise test statistics.
  • parametersOriginal parameters.
  • parametersParameters in permutation samples.
  • parameters_summaryOriginal parameter summary.
  • parameters_summary_MMean of each parameter in permutation sample.
  • parameters_summary_SDStandard deviation (SD) statistic in permutation slope.
  • parameters_summary_MADMean absolute deviation (MAD) statistic in permutation sample.
  • parameters_summary_MADLinear slope parameter in permutation sample.

References

Hildebrandt, A., Wilhelm, O., & Robitzsch, A. (2009). Complementary and competing factor analytic approaches for the investigation of measurement invariance. Review of Psychology, 16, 87-102.

See Also

For Examples see lsem.estimate.