Scott Weaver posted on Tuesday, February 07, 2006 - 12:22 pm
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 chi-square 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 chi-square 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 - 10:52 am
The exact condition for which MLR is correct are these: If [Y|X] is non-normal 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.
I am estimating a growth model with a continuous non-normal 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.