MEASURES OF VARIATION EXPLAINED BY BINARY REGRESSION(Categorical Data Analysis)

    • Kawai Norisuke
    • Biostatistics Group, Biometrics Department, Yamanouchi Pharmaceutical Co., Ltd.
    • Goto Masashi
    • Division of Statistical Science, Graduate School of Engineering Sciences, Osaka University

Abstract

In binary regression models we are interested in not only the parameter estimates and significance of explanatory variables, but also the degree to which variation in the response variable can be explained by explanatory variables. In this paper, we compare the behavior of proposed measures of explained variation for binary regression models through several case studies and indicate which measures should be accepted in practice. Furthermore, the importance of distinguishing measures of explained variation and goodness-of-fit is discussed. In conclusion, we recommend routine evaluation of the measures of explained variation in binary regression together with an exhaustive model which allows us to test the adequacy of simpler models such as the logistic model.

Journal

Journal of the Japanese Society of Computational Statistics   [List of Volumes]

Journal of the Japanese Society of Computational Statistics 15(2), 265-274, 2003-06  [Table of Contents]

Japanese Society of Computational Statistics

References:  22

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Codes

  • NII Article ID (NAID) :
    110001235180
  • NII NACSIS-CAT ID (NCID) :
    AA10823693
  • Text Lang :
    ENG
  • Article Type :
    REV
  • ISSN :
    09152350
  • Databases :
    CJP  NII-ELS 

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