A new approach to modeling positive random variables with repeated measures.
J Appl Stat
; 49(15): 3784-3803, 2022.
Article
em En
| MEDLINE
| ID: mdl-36324484
In many situations, it is common to have more than one observation per experimental unit, thus generating the experiments with repeated measures. In the modeling of such experiments, it is necessary to consider and model the intra-unit dependency structure. In the literature, there are several proposals to model positive continuous data with repeated measures. In this paper, we propose one more with the generalization of the beta prime regression model. We consider the possibility of dependence between observations of the same unit. Residuals and diagnostic tools also are discussed. To evaluate the finite-sample performance of the estimators, using different correlation matrices and distributions, we conducted a Monte Carlo simulation study. The methodology proposed is illustrated with an analysis of a real data set. Finally, we create an R package for easy access to publicly available the methodology described in this paper.
Texto completo:
1
Coleções:
01-internacional
Base de dados:
MEDLINE
Tipo de estudo:
Clinical_trials
/
Prognostic_studies
Idioma:
En
Revista:
J Appl Stat
Ano de publicação:
2022
Tipo de documento:
Article
País de afiliação:
Brasil
País de publicação:
Reino Unido