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 Katrin Lintorf posted on Thursday, September 10, 2009 - 2:12 am
Hi,
I am running a TYPE = TWOLEVEL COMPLEX RANDOM analysis and I am looking for an output that examines the assumptions (as described in Snijders & Bosker, 2004, p. 121: normal distribution and homoscedasticity of residuals etc.). Is there any possibility in Mplus to ensure that assumptions are met?
Thank you for any advice
Katrin
 Bengt O. Muthen posted on Thursday, September 10, 2009 - 1:08 pm
The MLR estimator is robust against deviations from the normality assumption. There is currently not an option to display residuals to check for homoscedasticity.
 Moh Yin Chang posted on Monday, September 14, 2009 - 7:24 am
Hi,

If I use the MODEL TEST: command in mplus for complex survey data, is the wald test adjusted for the complex sampling design?

Thanks.
 Linda K. Muthen posted on Monday, September 14, 2009 - 8:24 am
Yes.
 Moh Yin Chang posted on Monday, September 14, 2009 - 8:54 am
Can you please provide me the statistical reference for citation?
 Bengt O. Muthen posted on Monday, September 14, 2009 - 10:59 am
The Wald test uses as a "weight matrix" which is whatever covariance matrix is computed for the estimated parameters (see Tech3). With Type=Complex, the complex survey features are taken into account in Tech3. How that is done is shown in Asparouhov (2005) - the SEM article.

We don't have a reference for this aspect of Wald testing, mainly because this is using "first principles" of statistics. Perhaps you can refer to the article above and the UG.
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