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Estimating adjusted associations between random effects from multilevel models: the reffadjust package

Research output: Contribution to Journal/Magazine › Journal article › peer-review

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Standard

Estimating adjusted associations between random effects from multilevel models: the reffadjust package. / Palmer, Tom; Macdonald-Wallis, Corrie; Lawlor, Debbie et al.
In: Stata Journal, Vol. 14, No. 1, 2014, p. 119-140.

Research output: Contribution to Journal/Magazine › Journal article › peer-review

Harvard

Palmer, T, Macdonald-Wallis, C, Lawlor, D & Tilling, K 2014, 'Estimating adjusted associations between random effects from multilevel models: the reffadjust package', Stata Journal, vol. 14, no. 1, pp. 119-140. <http://www.stata-journal.com/article.html?article=st0327>

APA

Palmer, T., Macdonald-Wallis, C., Lawlor, D., & Tilling, K. (2014). Estimating adjusted associations between random effects from multilevel models: the reffadjust package. Stata Journal, 14(1), 119-140. http://www.stata-journal.com/article.html?article=st0327

Vancouver

Palmer T, Macdonald-Wallis C, Lawlor D, Tilling K. Estimating adjusted associations between random effects from multilevel models: the reffadjust package. Stata Journal. 2014;14(1):119-140.

Author

Palmer, Tom ; Macdonald-Wallis, Corrie ; Lawlor, Debbie et al. / Estimating adjusted associations between random effects from multilevel models : the reffadjust package. In: Stata Journal. 2014 ; Vol. 14, No. 1. pp. 119-140.

Bibtex

@article{002b4bae8e924c42a3b91b94b99ed0da,
title = "Estimating adjusted associations between random effects from multilevel models: the reffadjust package",
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.",
author = "Tom Palmer and Corrie Macdonald-Wallis and Debbie Lawlor and Kate Tilling",
year = "2014",
language = "English",
volume = "14",
pages = "119--140",
journal = "Stata Journal",
issn = "1536-867X",
publisher = "DPC Nederland",
number = "1",

}

RIS

TY - JOUR

T1 - Estimating adjusted associations between random effects from multilevel models

T2 - the reffadjust package

AU - Palmer, Tom

AU - Macdonald-Wallis, Corrie

AU - Lawlor, Debbie

AU - Tilling, Kate

PY - 2014

Y1 - 2014

N2 - 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.

AB - 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.

M3 - Journal article

VL - 14

SP - 119

EP - 140

JO - Stata Journal

JF - Stata Journal

SN - 1536-867X

IS - 1

ER -