Beta-binomial/Poisson regression models for repeated bivariate counts


Autoria(s): LORA, Mayra Ivanoff; SINGER, Julio M.
Contribuinte(s)

UNIVERSIDADE DE SÃO PAULO

Data(s)

20/10/2012

20/10/2012

2008

Resumo

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 (c) 2008 John Wiley & Sons, Ltd.

Identificador

STATISTICS IN MEDICINE, v.27, n.17, p.3366-3381, 2008

0277-6715

http://producao.usp.br/handle/BDPI/30529

10.1002/sim.3303

http://dx.doi.org/10.1002/sim.3303

Idioma(s)

eng

Publicador

JOHN WILEY & SONS LTD

Relação

Statistics in Medicine

Direitos

closedAccess

Copyright JOHN WILEY & SONS LTD

Palavras-Chave #bivariate counts #longitudinal data #overdispersion #random effects #regression models #DOSE-DEPENDENT NUMBER #POISSON-DISTRIBUTION #SUCCESS PROBABILITY #TRIALS #Mathematical & Computational Biology #Public, Environmental & Occupational Health #Medical Informatics #Medicine, Research & Experimental #Statistics & Probability
Tipo

article

original article

publishedVersion