|
|
Chi-square difference test is overpow... |
|
Message/Author |
|
Jane W. posted on Monday, January 07, 2013 - 11:41 pm
|
|
|
I'm testing a 4-factor solution against a second-order CFA with 4 lower-order factors. My sample sizes range from 1,000-9,000+, so I'd imagine that the chi-square diff tests are overpowered and much too sensitive to trivial differences. My questions: - Are there any large-sample alternatives to the chi-square difference test? - Or can I simply adopt a more stringent criterion (maybe p<.001 or p<.0001)? - Finally, can you point me to any articles on this topic? I appreciate any suggestions! Thank you! |
|
|
- Not really. You can try working with BIC - Becomes an arbitrary choice - One way to go is to work with less restrictive models as in Muthén, B. & Asparouhov, T. (2012). Bayesian SEM: A more flexible representation of substantive theory. Psychological Methods, 17, 313-335. which is on our web site. |
|
Back to top |
|
|