Message/Author 


Hello, I am seeking clarification of a sentence on pg. 340 under 'Missing Data Analysis' of the Mplus manual (version 3): "Robust standard errors and chisquare are available for all outcomes using the MLR estimator." This statement had led me to believe that if I specify Type=Missing and Estimator=MLR, then I would receive robust SE estimates under MAR. However, I was recently discussing this with someone who is certain that Mplus is implementing the procedure outlined in Yuan & Bentler (2000), to provide robust SE with missing data  but that Yuan & Bentler maintain that that they are assuming MCAR. Am I to assume that when data are nonnormal, the robust SE and chisquare statistic hold only under MCAR (though they may perform fairly well under MAR)? Thanks in advance for the clarification. Scott 

bmuthen posted on Wednesday, February 08, 2006  4:52 pm



The exact condition for which MLR is correct are these: If [YX] is nonnormal and the missing patterns are either MCAR or MAR but only predicted by X and not Y then MLR gives valid results. This condition in between MCAR and MAR. see for example the last two simulations in Web Note 2 http://statmodel.com/examples/webnotes/mc2c.html http://statmodel.com/examples/webnotes/mc2d.html 


I am estimating a growth model with a continuous nonnormal observed outcome that has some missing data. I am currently using the Type=Missing command in conjunction with Estimator=MLR, but this combination does not provide traditional fit indices to evaluate the fit of the growth curve. I have looked at the model using the MLR estimator with listwise deletion and it a linear growth model fits the data well. However, it seems weird to present fit statistics for a listwise deleted model and then use an MLR estimator to handle missingness for the substantive model. Suggestions? Thanks! Dustin 


Try TYPE=MISSING H1; You should then get the fit statistics you want. 


Thanks Bengt. Beginners mistake on my part. Can you suggest a reference that discusses the theoretical and statistical differences between using the "missing" and "missing h1" commands in Mplus? Dustin 


Sometimes estimating the unrestricted model can take time and be difficult when there is a lot of missing data so we allow the users the option of not estimating it or not. 

Back to top 