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Subject‐Specific and Population‐Averaged Continuation Ratio Logit Models for Multiple Discrete Time Survival Profiles
Author(s) -
Have Thomas R. Ten,
Uttal David H.
Publication year - 1994
Publication title -
journal of the royal statistical society: series c (applied statistics)
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.205
H-Index - 72
eISSN - 1467-9876
pISSN - 0035-9254
DOI - 10.2307/2986027
Subject(s) - statistics , logit , continuation , econometrics , mathematics , population , subject (documents) , logistic regression , survival analysis , demography , computer science , sociology , library science , programming language
SUMMARY Subject‐specific and population‐averaged continuation ratio logit models are presented for multivariate discrete time survival data. The models characterize data from a psychological experiment by using a quadratic polynomial relationship across time that depends on a time‐independent condition. A multivariate normal random effects distribution is imposed on intercept, linear and quadratic terms in the subject‐specific model, which is fitted by using a combination of Gibbs sampling and buffered stochastic substitution. Variance components that tend towards 0 are addressed in this context. In addition, generalized estimating equations estimates of the parameters in the population‐averaged model are compared with analogous estimates for the mixed effects model.