Beta-binomial/Poisson regression models for repeated bivariate counts
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 |
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 |