A unified approach for analyzing exchangeable binary data with applications to developmental toxicity studies.
Stat Med
; 28(20): 2580-604, 2009 Sep 10.
Article
em En
| MEDLINE
| ID: mdl-19548299
ABSTRACT
In this article, we present a general procedure to analyze exchangeable binary data that may also be viewed as realizations of binomial mixtures. Our approach unifies existing models and is practical and computationally easy. Resulting from completely monotonic functions, we introduce a rich family of parametric parsimonious binomial mixtures, including the incomplete Beta-, Gamma-, Normal-, and Poisson-binomial, generalizing the Beta-binomial. We show that the family is closed under convex linear combinations, products, and composites. We also give the moments and the Markov property of the family. With such distributions, we can perform statistical inference on correlated binary data and, in particular, overdispersed data. We propose a regression procedure that generalizes logistic regression. We provide a forward model selection procedure. We run a small simulation to validate the inclusion of the binomial distribution. Finally, we apply the proposed procedure to analyze the 2, 4, 5-Trichlorophenoxyacetic acid and E2 data and compare the results with existing procedures.
Texto completo:
1
Base de dados:
MEDLINE
Assunto principal:
Modelos Estatísticos
/
Efeitos Colaterais e Reações Adversas Relacionados a Medicamentos
Tipo de estudo:
Diagnostic_studies
/
Health_economic_evaluation
/
Risk_factors_studies
Limite:
Animals
Idioma:
En
Ano de publicação:
2009
Tipo de documento:
Article