Conditional pseudolikelihood methods for clustered ordinal, multinomial, or count outcomes with complex survey data-Reference-Cited by-同舟云学术

Conditional pseudolikelihood methods for clustered ordinal, multinomial, or count outcomes with complex survey data

Published:2012-09-13 Issue:8 Volume:32 Page:1325-1335
ISSN:0277-6715
Container-title:Statistics in Medicine
language:en
Short-container-title:Statist. Med.

Author:

Brumback Babette A.¹,Cai Zhuangyu¹,He Zhulin¹,Zheng Hao W.¹,Dailey Amy B.²

Affiliation:

1. Department of Biostatistics, College of Public Health and Health Professions, College of Medicine; University of Florida; Gainesville FL 32611 U.S.A.

2. Department of Health Sciences; Gettysburg College; Gettysburg PA 17325 U.S.A.

Funder

Department of Agriculture/Economic Research Service

Publisher

Wiley

Subject

Statistics and Probability,Epidemiology

Link

http://onlinelibrary.wiley.com/wol1/doi/10.1002/sim.5625/fullpdf

Reference24 articles.

1. Between- and within-cluster covariate effects in the analysis of clustered data;Neuhaus;Biometrics,1998

2. Separating between- and within-cluster covariate effects by using conditional and partitioning methods;Neuhaus;Journal of the Royal Statistical Society, Series B,2006

3. Adjusting for confounding by cluster using generalized linear mixed models;Brumback;Statistics and Probability Letters,2010

4. Efforts to adjust for confounding by neighborhood using complex survey data;Brumback;Statistics in Medicine,2010

5. Conditional logistic regression with survey data;Graubard;Statistics in Biopharmaceutical Research,2011

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