For illustrative purposes, let's assume that two groups of people (

**experts**vs.

**novices**) author a questionnaire with five scales (

**scale1**to

**scale5**). Let's further assume that I have reason to hypothesize that when these two questionnaires are given to the same sample of respondents, factor loadings for the novice questionnaire would be equally high as the factor loadings in the expert version. I want to be able to accept or reject this hypothesis with a single test and not conduct multiple tests for each scale.

My initial intuition would be to do this using confirmatory factor analysis, but I'm not familiar enough with CFA's to know exactly how.

My questions:

- Can I test this hypothesis by using CFA's and if so, how would I do it?
- Do you have practical tips on how to do this in R lavaan ?

- What other statistical frameworks and tests could be used?
- If this is too difficult to pull off, do you have any other suggestions to how the two versions could be compared with regard to structural validity?
- e.g. by averaging and comparing Cronbach's Alpha Coefficients (but what test would be used to do so)?
- e.g. by comparing experts and novice facets with Generalizability Theory (comparing G-coefficients, but again, what test would be used?)