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| MAR and Type=RANDOM with AUXILIARY |
 
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Hi all,
I have tried to track down other discussions of this topic and perhaps overlooked something, but couldn't find anything that completely answers my questions.
I am using TYPE=RANDOM in order to use TSCORES for analysis of a cohort-sequential design. I would like to also use the AUXILIARY command with the '(m)' option for missing data correlates, but it appears that I cannot: "The 'm' specifier in the AUXILIARY option is not available for TYPE=RANDOM."
Is there any way to overcome this limitation, e.g., with a newer version of Mplus? Or is there some fundamental analytic limitation here?
Thank you for any advice.
Very best,
John |
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| Try to capture the different cohorts using multiple-group analysis instead. See UGT ex 6.18. |
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I was looking at an example of a linear growth model with missing data on a continuous outcome using a missing data correlate to improve the plausibility of MAR in this link: http://www.statmodel.com/usersguide/chap11/ex11.1.html
I was wondering what are the hypothesis tested in relation to the auxiliary variables. In other words, how do I interpret the output regarding the auxiliary part of the model?
MODEL FIT INFORMATION
Number of Free Parameters 9
Loglikelihood Including the Auxiliary Part
H0 Value -1009.197
H1 Value -1007.232
Information Criteria Including the Auxiliary Part
Number of Free Parameters 15
Akaike (AIC) 2048.394
Bayesian (BIC) 2097.869
Sample-Size Adjusted BIC 2050.347
(n* = (n + 2) / 24)
Chi-Square Test of Model Fit
Value 3.930
Degrees of Freedom 5
P-Value 0.5595
Thanks! |
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The auxiliary part is saturated so does not impact the test of model fit. See the tech report
Auxiliary Variables Predicting Missing Data
on our website at
http://www.statmodel.com/techappen.shtml |
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