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2le
2004 Sep 12
1
Discrepency between R and MlwiN
...has an idea:
The data is two-level repeated measures data with measures nested within child. There are two measures per child. I've fit an unconditional growth model as in Singer and Willet (2003) that allows for variable intercepts
and slopes.
The R code for the analysis is:
model.uncgrowth.2lev <- lme(math ~ grade, mathdata, random=~grade|studentid)
The fixed effects estimates for the intercept and slope are the same between MlwiN and R. It's the random
effects estimates that differ. In particular, the residual error variance is ZERO using MlwiN and significantly
non-zero using R....