eqMI.bootstrap {equaltestMI}

Bootstrap procedure to test the equality of latent factor means using projection method

Description

Bootstrap procedure to test the equality of latent factor means using projection method

Usage

eqMI.bootstrap(..., B = 100, seed = 111)

Arguments

...

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

B

The number of bootstrap samples. Default at 100.

seed

The initial seed to generate bootstrap samples. Default at 111.

bootstrap

If bootstrap resampling is used to obtain empirical p-value of the statistics.

Details

Perform bootstrap procedure when testing the equality of latent means using projection method. Note that raw data must be available for bootstrap resampling to be performed. With the projection method, the cross-group intercepts are not required to be the same for further tests. If bootstrap resampling is used, the test statistics are not referred to chi-squared distributions but to bootstrapped empirical distributions for significance testing. Percentage bootstrap critical values are calculated. This process might be time-consuming if the model is complex or the number of bootstrap samples (B) is large.

Value

bootstrap p-values of the tests of common and specific factors.

References

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.

Examples

data(HolzingerSwineford)
semmodel<-'
L1 =~ V1 + V2 + V3
L2 =~ V4 + V5 + V6
L3 =~ V7 + V8
L4 =~ V9 + V10 + V11
'

run.bts <- eqMI.bootstrap(model = semmodel, data = HolzingerSwineford,
          group = "school", meanstructure = TRUE, B = 100, seed = 111)