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Binary Logistic Regression

  • David Aaron Maroof
Chapter

Abstract

Unlike linear regression, which is used to classify or predict values on a continuous variable (e.g., estimated premorbid intelligence), logistic regression attempts to classify or predict a discrete, categorical variable from among continuous and/or discrete predictors, such as whether or not a patient will be successful in cognitive rehabilitation (yes/no; the dichotomous criterion variable) based on premorbid intellectual functioning (the continuous predictor). Much like other sciences, clinical neuropsychology’s predilection for applying this model in research is tied to its inherent structure as a discipline, which involves the use of scientific nomenclature to describe cognition and behavior, and to compartmentalize syndromes into diagnostic entities.

Keywords

Multiple Sclerosis Logistic Regression Faculty Member Binary Logistic Regression Training Status 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

Bibliography

  1. Wright, R. E. (1995). Logistic regression. In L. G. Grimm & P. R. Yarnold (Eds.), Reading and Understanding More Multivariate Statistics (pp. 217–244). Washington, DC: American Psychological AssociationGoogle Scholar

Copyright information

© Springer Science+Business Media, LLC 2012

Authors and Affiliations

  • David Aaron Maroof
    • 1
  1. 1.OrlandoUSA

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