semTools (version 0.1-0)

measurementInvariance: Measurement Invariance Tests

Description

Testing measurement invariance across groups using a typical sequence of model comparison tests.

Usage

measurementInvariance(..., strict = FALSE, quiet = FALSE)

Arguments

...

The same arguments as for any lavaan model. See cfa for more information.

strict

If TRUE, the sequence requires `strict' invariance. See details for more information.

quiet

If TRUE, a summary is printed out containing an overview of the different models that are fitted, together with some model comparison tests.

Value

• Invisibly, all model fits in the sequence are returned as a list.

code

strict = TRUE

enumerate

1. Model 1: configural invariance. The same factor structure is imposed on all groups.

item

• Model 2: weak invariance. The factor loadings are constrained to be equal across groups.
• Model 3: strong invariance. The factor loadings and intercepts are constrained to be equal across groups.
• Model 4: strict invariance. The factor loadings, intercepts and residual variances are constrained to be equal across groups.
• Model 5: The factor loadings, intercepts, residual variances and means are constrained to be equal across groups.

url

http://www.statmodel.com/chidiff.shtml

Details

If strict = FALSE, the following four models are tested in order:

1. Model 1: configural invariance. The same factor structure is imposed on all groups.

Model 2: weak invariance. The factor loadings are constrained to be equal across groups. Model 3: strong invariance. The factor loadings and intercepts are constrained to be equal across groups. Model 4: The factor loadings, intercepts and means are constrained to be equal across groups.

References

Vandenberg, R. J., and Lance, C. E. (2000). A review and synthesis of the measurement invariance literature: Suggestions, practices, and recommendations for organizational research. Organizational Research Methods, 3, 4-70.

Examples

HW.model <- ' visual =~ x1 + x2 + x3
              textual =~ x4 + x5 + x6
              speed =~ x7 + x8 + x9 '

measurementInvariance(HW.model, data=HolzingerSwineford1939, group="school")