English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Global: Zendy Plus annual

Presents the access of premium content as premium feature

Premium Content

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Global: Zendy Tools annual

Global: Zendy Free Plan

Global: Zendy Tools monthly

Global: Zendy Plus monthly

In Lora and Singer (Statistics in Medicine, 2008), we proposed a Beta-Binomial/ Poisson p-variate model to analyze data from a study which consists in counting the number of trials and successes of a manual exercise in one minute periods, done by Parkinson’s disease patients, before and after a training. The purpose was to verify if the training improves the number of trials and the percentage of success, which emphasizes the bivariate aspect of the problem. This model considers these characteristics, uses an adequate distribution to count data and settles the overdispersion suggested in the number os successes. As a generalization, initially, we propose a Beta-Binomial/Poisson-Gama model which also settles the overdispersion suggested by the total number of trials, besides includes possible different covariances between total trial counts in different evaluation instants. In this new model, we introduce a parameter that links the total trials with the success probability, making it even more general. We obtain maximum likelihood estimators for the parameters using an Newton-Raphson algorithm. We consider another data from the same study to illustrate the proposal methodology. Key-words: bivariate counts, longitudinal data, overdispersion, random effects, regression models

Modelos Beta-Binomial/Poisson-Gama para contagens bivariadas repetidas