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Analysis of ulcer data using hierarchical generalized linear models
Author(s) -
Lee Youngjo,
Nelder John A.
Publication year - 2001
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/sim.978
Subject(s) - random effects model , construct (python library) , multilevel model , statistics , measure (data warehouse) , econometrics , hierarchical database model , generalized linear model , linear model , mathematics , computer science , medicine , data mining , meta analysis , programming language
Abstract In multi‐centre clinical trials, heterogeneities in individual hospital treatment effects can be modelled as random effects. Estimates of the individual hospital treatment effects and estimate of the mean treatment effect, allowing for the presence of overall hospital differences, are required, together with some measure of their uncertainty. Systematic inferences from the hierarchical‐likelihood are now possible, using hierarchical generalized linear models. We show how to construct profile likelihoods for the treatment effects of individual hospitals. Copyright © 2002 John Wiley & Sons, Ltd.