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Model selection in logistic joinpoint regression with applications to analyzing cohort mortality patterns
Author(s) -
Czajkowski Michal,
Gill Ryan,
Rempala Grzegorz
Publication year - 2007
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.3017
Subject(s) - logistic regression , selection (genetic algorithm) , cohort , computer science , regression , model selection , cohort effect , statistics , econometrics , regression analysis , artificial intelligence , machine learning , mathematics
We consider a general model for anomaly detection in a longitudinal cohort mortality pattern based on logistic joinpoint regression with unknown joinpoints. We discuss backward and forward sequential procedures for selecting both the locations and the number of joinpoints. Estimation of the model parameters and the selection algorithms are illustrated with longitudinal data on cancer mortality in a cohort of chemical workers. Copyright © 2007 John Wiley & Sons, Ltd.