Beta-binomial/Poisson regression models for repeated bivariate counts.
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.
Departamento de Estatística, IME, Universidade de São Paulo, Caixa Postal 66281, São Paulo, SP 05311-970, Brazil.
Mayra Ivanoff
MI
Lora
Julio M
JM
Singer
D000704:Analysis of Variance; D016010:Binomial Distribution; D006801:Humans; D016013:Likelihood Functions; D015233:Models, Statistical; D009043:Motor Activity / Q000502:physiology; D010300:Parkinson Disease / Q000503:physiopathology; D026741:Physical Therapy Modalities; D016012:Poisson Distribution; D012044:Regression Analysis