How does Mplus handle non-normal model? PreviousNext
Mplus Discussion > Multilevel Data/Complex Sample >
 shige posted on Saturday, March 20, 2004 - 4:58 am
MQL, PQL, quaduature, or laplace?
 bmuthen posted on Saturday, March 20, 2004 - 12:39 pm
Version 3 uses maximum-likelihood using numerical integration (quadrature). Censored and categorical outcomes can be done both by ML and a weighted least squares (limited information) estimator.
 shige posted on Wednesday, March 24, 2004 - 7:19 am
Will adaptive quadrature be available as an option?
 Linda K. Muthen posted on Wednesday, March 24, 2004 - 12:23 pm
 shige posted on Wednesday, March 24, 2004 - 4:31 pm
That's great! I am looking forward to it.
 Anonymous posted on Friday, January 28, 2005 - 9:23 pm
I'm afraid this censored regression/integration approach is a bit of a black box to me. Would someone more knowledgeable be so kind as to list some references for the unwashed?
 Linda K. Muthen posted on Saturday, January 29, 2005 - 2:11 am
Whenever the density for an observation does not have a closed form, numerical integration of the latent continuous variables is required. For binary outcomes, see Bock and Aitkin in Psychometrika. I don't have the references handy. The response here is logit not censored but the idea is the same. For information about censored outcomes, see:

Maddala, G.S. (1983). Limited-dependent and qualitative variables in econometrics. Cambridge: Cambridge University Press.
 Marco posted on Thursday, January 26, 2006 - 12:17 pm
Hello Linda, hello Bengt,

when estimating sig-between with MLR, does that imply that the non-normality of the raw data S-T is "removed" in sig-between? It seems to be important, since sig-between could only be analyzed with non-robust ML.

 Linda K. Muthen posted on Thursday, January 26, 2006 - 2:23 pm
Sigma between is the same whether you use ML or MLR. The values have not been estimated taking non-normality into account.
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