Estimating adjusted associations between random effects from multilevel models: The reffadjust package
Tom M. Palmer
Division of Health Sciences
Warwick Medical School
University of Warwick
Coventry, UK
[email protected]
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Corrie M. Macdonald-Wallis
MRC and University of Bristol Integrative Epidemiology Unit
School of Social and Community Medicine
University of Bristol
Bristol, UK
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Debbie A. Lawlor
MRC and University of Bristol Integrative Epidemiology Unit
School of Social and Community Medicine
University of Bristol
Bristol, UK
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Kate Tilling
School of Social and Community Medicine
University of Bristol
Bristol, UK
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Abstract. We describe a method to estimate associations between random effects
from multilevel models. We provide two new postestimation commands,
reffadjustsim and reffadjust4nlcom, which are distributed as the reffadjust
package. These commands produce the estimates and their associated confidence
intervals. The commands are used after official Stata multilevel model estimation
commands mixed, meqrlogit, and meqrpoisson (formerly named xtmixed,
xtmelogit, and xtmepoisson, respectively, before Stata 13) and with models fit in
the MLwiN statistical software package via the runmlwin command. We demonstrate
our commands with several simulated datasets and for a bivariate outcome
model investigating the relationship between weight and mean arterial pressure
in pregnant women using data from the Avon Longitudinal Study of Parents and
Children. Our method and commands help to improve the interpretability of estimated
random-effects variance components from multilevel models.
View all articles by these authors:
Tom M. Palmer, Corrie M. Macdonald-Wallis, Debbie A. Lawlor, Kate Tilling
View all articles with these keywords:
reffadjust, reffadjustsim, reffadjust4nlcom, meqrlogit, meqrpoisson, mixed, multilevel models, runmlwin, xtmelogit, xtmepoisson, xtmixed, ALSPAC
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