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POPULATION‐AVERAGED AND CLUSTER‐SPECIFIC MODELS FOR CLUSTERED ORDINAL RESPONSE DATA
Author(s) -
TEN HAVE THOMAS R.,
RICHARD LANDIS J.,
HARTZEL JONATHAN
Publication year - 1996
Publication title -
statistics in medicine
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.996
H-Index - 183
eISSN - 1097-0258
pISSN - 0277-6715
DOI - 10.1002/(sici)1097-0258(19961215)15:23<2573::aid-sim389>3.0.co;2-o
Subject(s) - logit , logistic regression , statistics , ordinal regression , econometrics , context (archaeology) , ordered logit , mathematics , ordinal data , population , cluster (spacecraft) , binary data , estimation , binary number , computer science , demography , geography , economics , arithmetic , archaeology , management , sociology , programming language
We compare population‐averaged and cluster‐specific models for clustered ordinal data. We consider generalized estimating equations and constrained equations maximum likelihood estimation of population‐averaged cumulative logit regression models, and mixed effects estimation of cluster‐specific cumulative logit regression models. A previously reported relationship between population‐averaged and cluster‐specific parameters for the binary logistic link appears to hold for analogous parameters under the cumulative logit link. We address these issues in the context of data from two cross‐over clinical trials.