Description Usage Arguments Details Value References Examples
View source: R/eqMI.projection.R
Perform projection method for testing the equality of latent means without requiring the equality of cross-group intercepts to hold.
1  | 
... | 
 The same arguments as for any lavaan model. See  Users must explicitly specify the name of the input elements for this function to catch. For example, specify 'data = HolzingerSwineford' instead just 'HolzingerSwineford'.  | 
Perform projection method for testing the equality of two latent means without requiring the cross-group intercepts to be the same. A validity index is provided as the proportion of the differences in manifest variables intercepts explained by latent mean differences as a gauge of the quality of measurements.
A list is returned with:
fit.metrictest of metric invariance (factor loadings). This is a prerequisite for testing equality of latent means.
mvdif.testt tests of the cross-group sample means for each variable.
chi.statThree chi-square tests for intercepts, common factors, and specific factors. chi.stat will be needed for equivalence testing.
common.testt tests of common factors for each variable.
specific.testt tests of specific factors for each variable.
latent.testt tests of latent means
V.indexvalidity index
Pmatprojection matrix of intercepts into the space of common factors
Qmatprojection matrix of intercepts into the space of specific factors
Yuan, K. H., & Chan, W. (2016). Measurement invariance via multigroup SEM: Issues and solutions with chi-square-difference tests. Psychological methods, 21(3), 405-426.
1 2 3 4 5 6 7 8 9  | data(HolzingerSwineford)
semmodel<-'
L1 =~ V1 + V2 + V3
L2 =~ V4 + V5 + V6
L3 =~ V7 + V8
L4 =~ V9 + V10 + V11
'
run.proj <- eqMI.projection(model = semmodel, data = HolzingerSwineford,
          group = "school", meanstructure = TRUE)
 | 
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.