[R-sig-ME] Random intercept for subgroup
Luca Corlatti
luca.corlatti at boku.ac.at
Mon Dec 19 09:50:32 CET 2016
Dear list members,
suppose I have a case study with 2 different populations, A and B. For
both groups I have data on body mass, length and sex of a given species.
For group A data were collected over different years, and I may be
interested to include the cohort in the analysis as a random effect,
while for group B I have no such information. The dataframe would look
something like:
Pop Coh Weight Length Sex
A 2010 12.1 34 m
A 2011 13.4 42 m
A 2012 10.3 36 f
A 2010 10.5 32 m
A 2013 12.1 37 f
A 2014 12.4 35 f
A 2011 14.1 32 f
...
B NA 13.1 36 m
B NA 10.5 35 f
B NA 12.4 32 fB NA 12.6 35 m
…
Let's now suppose I want to investigate the relationship between Weight
and Length, for males and females of different populations, i.e. using a
3-way interaction. Would it still be possible to run the analysis in
one single mixed model with a random intercept (cohort) only for group
A, or would I be forced to use 2 different models, one for population A
(random intercept model) and one for population B (fixed effect model)?
With my actual dataset, a lmer (Weight~Length*Sex*Pop + (1 + Pop | Coh)
) fitted changing NA to 1 seems to give the same estimate for Population
B as the lm (Weight~Length*Sex*Pop), but I am not quite sure this is the
correct approach.
Thanks,
Luca
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