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| Author(s): |
Renata Pelissari
Total Authors: 1
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| Document type: | Master's Dissertation |
| Press: | São Carlos. |
| Institution: | Universidade de São Paulo (USP). Instituto de Ciências Matemáticas e de Computação (ICMC/SB) |
| Defense date: | 2009-09-18 |
| Examining board members: |
Dorival Leão Pinto Junior;
Mário de Castro Andrade Filho;
Jose Galvao Leite
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| Advisor: | Dorival Leão Pinto Junior |
| Field of knowledge: | Physical Sciences and Mathematics - Probability and Statistics |
| Indexed in: | Banco de Dados Bibliográficos da USP-DEDALUS; Biblioteca Digital de Teses e Dissertações - USP |
| Location: | Universidade de São Paulo. Instituto de Ciências Matemáticas e de Computação. Biblioteca Prof. Achille Bassi; T; P384ae |
| Abstract | |
In several applications, we want to analyze the behavior of multinomial datas over the time and its relationship with important factors. The classic methods commonly used for multinomial regression models are based in the generalized linear model framework. However, this models presents some disadvantages such that: it does not admit the incidence of zeros in any category, the assumption of proportionality of odds ratio and the fact that they are not appropriate models to analyze censored data. For multinomial data analyses with this characteristics, we propose a model that it is an extension of the multiplicative intensity model developed by Aalen to random multinomial variables. Therefore, instead of modeling the categorical probabilities, as in the classics methods, we modeled the intensity fuction associated with the multinomial variable. Using the martingale criterion, we estimate the models parameters and propose hypothesis testing for these parameters for one and two populations. The test for comparing two populations is based in the logrank statistics (AU) | |