Dissertação
A necessidade de classificações repetidas no modelo de regressão logística com erros na variável resposta
Fecha
2019-02-04Autor
Danilo Gilberto de Oliveira Valadares
Institución
Resumen
Maximum likelihood estimators for the logistic regression model with misclassification in the response variable are extremely biased when error probabilities are ignored. If misclassification parameters are incorporated in the likelihood function, the bias of the estimators will be satisfactorily reduced, however, there would be a considerable increase in variability, which would reduce the quality of the decision-making process. To minimize the problem, there is a need to introduce additional information. It will be demonstrated that the realization of repeated measures in the response variable, or in part of it, can reduce bias and variability of the estimators, simultaneously.