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 Malcolm Cunningham posted on Monday, November 28, 2011 - 12:35 pm
I have 107,025 children's responses to standardized mathematics instruments administered in three waves (wave 1 - 37 items; wave 2 - 36 items; wave 3 - 31 items). I am conducting the analysis in the sequence: EFA, LCA, FMA, LTA. My ultimate concern is with model stability throughout the process because it seems to me that with each step in the process, the solution space inevitably increases.

I am concerned that the total possible response pattern space - the

distribution of possible response patterns - is much much larger than my

sample size (2^37 vs 2^16.076 (approx 107,025) for wave 1). In this

respect, my model may be mis-specified. I see one of three possible directions

to mitigate my unease.

1. Take a number of random samples (say 5,000) of the original linked

data-set and run parallel EFA, LCA, FMA, and LTA analyses. Bump up the BLRT

and LMRLRT random draws. Compare.

2. Reduce the number of items per wave to <= 16 (i.e., 2^16

= 65,536 which is < 107,025) run entire sample.

3. Reduce the number of items per wave to <= 16, take random samples (say 5,000) and compute estimates. Compare.

Could you please advise me as to which of these (or, perhaps a new one I

haven't considered) might satisfy my concerns?
 Linda K. Muthen posted on Monday, November 28, 2011 - 5:31 pm
Number 1 sounds good.
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