Practical issues in using generalized estimating equations for inference on transitions in longitudinal data: What is being estimated?-Reference-Cited by-同舟云学术

Practical issues in using generalized estimating equations for inference on transitions in longitudinal data: What is being estimated?

Published:2018-11-08 Issue:6 Volume:38 Page:903-916
ISSN:0277-6715
Container-title:Statistics in Medicine
language:en
Short-container-title:Statistics in Medicine

Author:

Bible Joe¹,Albert Paul S.²^ORCID,Simons-Morton Bruce G.³^ORCID,Liu Danping²^ORCID

Affiliation:

1. Department of Mathematical Sciences; Clemson University; Clemson South Carolina

2. Division of Cancer Epidemiology and Genetics, Biostatistics Branch; National Cancer Institute; Bethesda Maryland

3. Health Behavior Branch; Eunice Kennedy Shriver National Institute of Child Health and Human Development; Rockville Maryland

Funder

National Institutes of Health

Eunice Kennedy Shriver National Institute of Child Health and Human Development

National Cancer Institute

Publisher

Wiley

Subject

Statistics and Probability,Epidemiology

Link

http://onlinelibrary.wiley.com/wol1/doi/10.1002/sim.8014/fullpdf

Reference16 articles.

1. Longitudinal data analysis using generalized linear models;Liang;Biometrika,1986

2. A comparison of population average and random-effect models for the analysis of longitudinal count data with baseline information;Crouchley;J R Stat Soc A Stat Soc,1999

3. A comparison of GEE and random effects models for distinguishing heterogeneity, nonstationarity and state dependence in a collection of short binary event series;Crouchley;Stat Model,2001

4. Bootstrapping GEE models for fMRI regional connectivity;D'Angelo;Neuroimage,2012

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