Message/Author 

Anonymous posted on Monday, March 19, 2012  11:17 am



I've got a few questions about the MLR output: The Mplus output for MLR includes, if I am correct, • Regression coefficient estimates using maximum likelihood estimation • Robust standard errors computed with HuberWhite 'sandwich' estimator • Robust chisquare test of model fit using an extension of the YuanBentler T2 test statistic • MLR uses Full Information Maximum Likelihood Estimation to handle missing data • Hypothesis is tested by computing the ratio of the estimate by its standard error ("Est./S.E."), and corresponding pvalue. If I am correct, this would be my ttest/ztest? ª ª If if this my ttest/ztest, would it be more appropriate to report as a ttest or a ztest (n = 326)? Does this seem accurate, and is there anything I should probably know from this output? Also, just to clarify, does this method still count as 'multiple linear regression'? I saw someone commented in the forum saying that it used logistic regression, so now I am doubting I should using this in the first place. I would appreciate clarification/confirmation on this, please. Thanks in advance, JL 


The ratio of the parameter estimate to its standard error is a ztest in large samples. MLR estimates linear regression if the dependent variable is continuous and logistic regression if the dependent variable is categorical. 

Anonymous posted on Monday, March 19, 2012  4:43 pm



Ah I see, that's genius (how it knows which one to use). ztest it is then. So it is safe to say I would still be able this regression equation, Y = i + aX + bM + cXM + E? 


Yes. 

Michael posted on Tuesday, May 29, 2012  4:29 am



Dear Professor/s, I´m new to Mplus. I have use the MLRestimator, because of the nonnormality in the indicatorvariables. Now I´m trying to find some guilines for the cutoff criterias for the fit indexes. Is it ok to use the suffestions from "Hu & Betnler (1999). Cutoff Criteria for Fit Indexes in Covariance Structure Analysis: Conventional Criteria Versus New Alternatives, SEM 6(1), 155". They appear to be only for the MLEstimator. In other words: Are the recommendations for the cutoff criterias for MLestimator the same as for MLR? Many Thanks in advance Michael 


I don't believe there have been any studies specific to MLR. The Hu and Bentler cutoffs are probably the best you can do. 

Michael posted on Tuesday, May 29, 2012  10:46 am



Thank you very much for the quick response! 


Hi there, I'm running a series of Bivariate latent change score models and am wondering whether to use ml or mlr estimation. My n=200. My dependent variables are non normally distributed (skewness around 23, kurtosis between 2 and 13) and data are MAR (12 missing data patterns, lowest covariance coverage is .861 ). Is mlr recommended in this case? Or is ml adequate? Thank you! 


I would use MLR. It is robust to nonnormality. ML is not. 

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