Measurement Invariance Testing - Statistical Analyst -

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I think the most appropriate test for invariability is an analysis of variance, which is know as ANOVA in statistics. In addition to that, it also would be worth considering to conduct a monte carlo simulation upon the available data assuming that the invariability are due to random error and these error have a nature of normal distribution. I would like to assist you. Kindly advice me further instructions. Thank you very much. Will be waiting your message...

I have done CFA many times and I can do Measurement Invariance Testing applying the steps of Comşa (2019): Step 0: Testing for the configural (CFA) model for each group separately. Ideally, the model should be the same for all groups or contains minor variations. Step 1: Testing for the configural model for all groups together (multigroup model). If the fit indices are above the rules of thumb the model has a similar factor structure, but it is not necessarily equivalent across groups. Step 2: Testing for metric invariance. Constrain the factor loadings to be equal across groups and check the fit of the metric model. Step 3: Testing for scalar invariance. Constrain the intercepts to be equal across groups and check the fit of the scalar model. Step 4: Chose a reference group and set its mean to zero. Compute and compare the mean of latent variable across groups.

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