ANÁLISIS DE DIAGNÓSTICO EN EL MODELO DE REGRESIÓN LOGÍSTICA: UNA APLICACIÓN

Authors

  • Olga Solano Dávíla Facultad de Ciencias Matemáticas - Universidad Nacional Mayor de San Marcos – Lima - Lima – Perú
  • Agustina Ramírez Torres Facultad de Ciencias Naturales de la Universidad Nacional Federico Villarreal – Lima – Perú
  • Félix Manuel Bartolo Gotarate Facultad de Ciencias Matemáticas - Universidad Nacional Mayor de San Marcos – Lima - Lima – Perú
  • Orlando Giraldo Laguna Facultad de Ciencias Matemáticas - Universidad Nacional Mayor de San Marcos – Lima - Lima – Perú
  • Alfredo Salinas Moreno Facultad de Ciencias Matemáticas - Universidad Nacional Mayor de San Marcos – Lima - Lima – Perú

DOI:

https://doi.org/10.15381/pes.v10i1.9431

Keywords:

Multivariate technic, logistic Regression model, Diagnostic analysis, analysis of residues, analysis of influence.

Abstract

Logistic regression is a multivariate technique very important for its applications in different areas of knowingness and its applications has been growing more. In clinical and epidemiological research, in particular in a study coronary illness, analysis of logistic regression has been applied for first time around 60 years old (lB) . In studies of logistic regression, it is frequent that a group of observations can be outliers. In the construction of logistic regression models is important to examine the observations to detect the existence of one or more observations that is controlling important properties of the modelo We present a discussion on diagnostic to logistic regression model (5), on factors of risk in illness of bone.

Author Biography

  • Agustina Ramírez Torres, Facultad de Ciencias Naturales de la Universidad Nacional Federico Villarreal – Lima – Perú

    Facultad de Ciencias Naturales de la Universidad Nacional Federico Villarreal – Lima – Perú

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Published

2007-07-16

Issue

Section

Artículos

How to Cite

ANÁLISIS DE DIAGNÓSTICO EN EL MODELO DE REGRESIÓN LOGÍSTICA: UNA APLICACIÓN. (2007). Pesquimat, 10(1). https://doi.org/10.15381/pes.v10i1.9431