[R-sig-ME] Missing values in lmer vs. HLM

[Carpenter, Tom]

All,

I have a paper in which we are using a within-person model using multi-level modeling. I ran the models in lmer in R, although we had a substantial portion of people for whom at least one observation is still missing. My understanding is that the default is to drop that person entirely (e.g., na.action=na.omit) ….is that correct? My understanding was that the HLM software (e.g., by SSI) and most other multi-level modeling programs can still run the models based on the remaining observations (e.g., you may have 4 out of 5 observations per person and still be able to run the model).

I would love to know if it is possible to do that in lmer or if some solution is present. For example, is it possible to use FIML in lmer? Advice for handling this situation would be appreciated, as I’m new to lmer!

Best,


Tom Carpenter, Ph.D.
Assistant Professor, Psychology
Seattle Pacific University
3307 3rd Ave W. Suite 107,
Seattle, WA, 98119
tcarpenter at spu.edu<mailto:tcarpenter at spu.edu>
Office: (206) 281-2916
Fax: (206) 281-2695













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