
Message/Author 

JW posted on Sunday, November 04, 2007  9:32 am



Hi, I'm using a MLM estimator with data that is missing at random. I've imputed the following in the VARIABLE command VARIBALE: USEVAR ARE DSRS SSSMINUS CNCEQ CESBQ; MISSING ARE ALL (999); In the analysis command I entered: ANALYSIS: ESTIMATOR IS MLM; TYPE=MISSING H1; If I don't enter TYPE=Missing, my N drops and it seems to do a listwise deletion. If I include the Type=missing, it uses the full sample, but I get the following error: *** ERROR in Analysis command Estimator MLM is not allowed with TYPE = GENERAL MISSING. Default will be used. 1 ERROR(S) FOUND IN THE INPUT INSTRUCTIONS How do I include the full sample, using MLM and account for missing data? 

Paul Silvia posted on Sunday, November 04, 2007  10:40 am



For TYPE = GENERAL MISSING H1 and continuous outcomes, only ML, MLR, and MLF are available (see User Guide p. 424). If you use the MISSING option, then the ML estimator is fullinformation ML, so ML or MLR is probably what you want here. 

JW posted on Monday, November 05, 2007  5:37 pm



Thanks. I think I'm confused as I do have nonnormal data, and should use the robust maximum likelihood estimator, right? How should I handle missing data with nonnormal, continuous data? 

Paul Silvia posted on Monday, November 05, 2007  6:12 pm



One would need to know a lot about the nature of the nonnormality (as well as other assumptions that may be unmet), but my preference would be to add the BOOTSTRAP option to the ANALYSIS command, a la: TYPE = MISSING H1; ESTIMATOR = ML; BOOTSTRAP = 1000; (see UG p. 434). And under OUTPUT, add: CINTERVAL (BOOTSTRAP); This will handle the missing data as well as give you bootstrapped standard errors and confidence intervals. 

JW posted on Tuesday, November 06, 2007  5:25 am



Thanks! This is helpful. James. 

JW posted on Wednesday, November 07, 2007  5:11 am



Actually, I do have a f/u up question. Is there a way to include missing data with MLM estimator? So, when I did the analyses with boostrapping as you mentioned above, the full N was used, but when just with MLM as an estimator and no missing data command (as the error message occurs), cases were not included and my N dropped. 


No. Only listwise deletion is allowed with MLM. 

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