Dear R experts,
I had a question which may not be directly relevant to R but I will be
grateful if you can give me some advices.
I ran a two-level multilevel model for data with repeated measurements over
time, i.e. level-1 the repeated measures and level-2 subjects. I could not
get convergence using lme(), so I tried MLwiN, which eventually showed the
level-2 variances (random effects for the intercept and slope) were
negative values. I know this is known as Heywood cases in the structural
equation modeling literature, but the only discussion on this problem in
the literature of multilevel models and random effects models I can find is
in the book by Prescott and Brown.
Any suggestion on how to solve this problem will be highly appreciated.
Many thanks.
With best regards,
Yu-Kang
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