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METHODS OF ESTIMATION IN MULTIPLE LINEAR REGRESSION: APPLICATION TO CLINICAL DATA

Coelho-Barros, Emílio Augusto ; Priscila Angelotti Simões ; Achcar, Jorge Alberto ; Martinez, Edson Zangiacomi ; Shimano, Antônio Carlos

Revista Colombiana de estadística, 2008-06, Vol.31 (1), p.111 [Periódico revisado por pares]

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Título:
METHODS OF ESTIMATION IN MULTIPLE LINEAR REGRESSION: APPLICATION TO CLINICAL DATA
Autor: Coelho-Barros, Emílio Augusto ; Priscila Angelotti Simões ; Achcar, Jorge Alberto ; Martinez, Edson Zangiacomi ; Shimano, Antônio Carlos
É parte de: Revista Colombiana de estadística, 2008-06, Vol.31 (1), p.111
Descrição: In this paper, we show different parameters estimation forms for multiple linear regression model. We used clinical data, where the interest was to verify the relationship among the mechanical assay maximum stress with femoral mass, femoral diameter and group of ovariectomized Wistar rats. We used three inference methods: Classic inference, based on the least square method; bayesian inference, based on the Bayes theorem; and bootstrap inference, based on resampling processes.
Editor: Bogota: Universidad Nacional de Colombia
Idioma: Inglês

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