Métodos de estimação em regressão linear múltipla: aplicação a dados clínicos

• EMÍLIO AUGUSTO COELHO-BARROS ^[1] ; PRISCILA ANGELOTTI SIMÕES ^[1] ; JORGE ALBERTO ACHCAR ^[1] ; EDSON ZANGIACOMI MARTINEZ ^[1] ; ANTÔNIO CARLOS SHIMANO ^[1]
  1. [1] Universidade de São Paulo

     Universidade de São Paulo

     Brasil

     
• Localización: Revista Colombiana de Estadística, ISSN-e 2389-8976, ISSN 0120-1751, Vol. 31, Nº. 1, 2008, págs. 111-129
• Idioma: portugués
• Títulos paralelos:
  • Methods of estimation in multiple linear regression: application to clinical data
• Enlaces
  • Texto completo
• Resumen
  • English

    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.

  • português

    Nesse artigo, tem-se o interesse em avaliar diferentes estratégias de estimação de parâmetros para um modelo de regressão linear múltipla. Para a estimação dos parâmetros do modelo foram utilizados dados de um ensaio clínico em que o interesse foi verificar se o ensaio mecânico da propriedade de força máxima (EM-FM) está associada com a massa femoral, com o diâmetro femoral e com o grupo experimental de ratas ovariectomizadas da raça Rattus norvegicus albinus, variedade Wistar. Para a estimação dos parâmetros do modelo serão comparadas três metodologias: a metodologia clássica, baseada no método dos mínimos quadrados; a metodologia Bayesiana, baseada no teorema de Bayes; e o método Bootstrap, baseado em processos de reamostragem.

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