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Beta‐binomial/Poisson regression models for repeated bivariate counts
Author(s) -
Lora Mayra Ivanoff,
Singer Julio M.
Publication year - 2008
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.3303
Subject(s) - poisson regression , negative binomial distribution , bivariate analysis , univariate , statistics , poisson distribution , overdispersion , count data , regression analysis , beta (programming language) , binomial regression , regression , econometrics , multivariate statistics , mathematics , computer science , medicine , population , environmental health , programming language
Abstract We analyze data obtained from a study designed to evaluate training effects on the performance of certain motor activities of Parkinson's disease patients. Maximum likelihood methods were used to fit beta‐binomial/Poisson regression models tailored to evaluate the effects of training on the numbers of attempted and successful specified manual movements in 1 min periods, controlling for disease stage and use of the preferred hand. We extend models previously considered by other authors in univariate settings to account for the repeated measures nature of the data. The results suggest that the expected number of attempts and successes increase with training, except for patients with advanced stages of the disease using the non‐preferred hand. Copyright © 2008 John Wiley & Sons, Ltd.