semTools (version 0.4-11)

measurementInvariance: Measurement Invariance Tests

Description

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

Usage

measurementInvariance(..., std.lv = FALSE, strict = FALSE, quiet = FALSE,
fit.measures = "default", method = "satorra.bentler.2001")

Arguments

...

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

std.lv

If TRUE, the fixed-factor method of scale identification is used. If FALSE, the first variable for each factor is used as marker variable.

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.

fit.measures

Fit measures used to calculate the differences between nested models.

method

The method used to calculate likelihood ratio test. See lavTestLRT for available options

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.

See Also

longInvariance for the measurement invariance test within person; partialInvariance for the automated function for finding partial invariance models

Examples

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

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