ML and WLSMV estimates PreviousNext
Mplus Discussion > Categorical Data Modeling >
Message/Author
 Adrienne Tin posted on Wednesday, April 12, 2006 - 7:59 am
I have a very simple regression with a categorical outcome. ML and WLSMV give very different estimates. How should I interpret them?

ML estimates of the predictor

Estimates 0.513
S.E. 0.249
StdYX 0.272

Thresholds
Outcome$1 2.049

Why is StdYX differ from the Estimates?

WLSMV estimates (same model)
Estimates 0.283
S.E. 0.143
StdYX 0.274


Why is the WLSMV estimate (0.283) so different from the ML estimate (0.513)?

Thanks in advance.
 Linda K. Muthen posted on Wednesday, April 12, 2006 - 8:06 am
In Mplus, the default for maximum likelihood is logistic regression and the default for weighted least square is probit regression. These differ by a scale of approximately 1.7.
 Adrienne Tin posted on Wednesday, April 12, 2006 - 3:05 pm
Hi, Linda, thanks for the response. Now I remember reading about WLSMV and probit model somewhere.

Could you also explain why stdYX is different from the estimate?
I read that they are different only when there are multiple dependent variables. In this simple model, there is only one dependent variable.

Thanks
 Linda K. Muthen posted on Thursday, April 13, 2006 - 9:37 am
As long as the variances of y and x are not one, STDYX will be different that the raw parameter estimate for both univariate and multivariate regression.
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