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Logistic Regression

In: Multivariate Analysis

Author

Listed:
  • Klaus Backhaus

    (University of Münster)

  • Bernd Erichson

    (Otto-von-Guericke-University Magdeburg)

  • Sonja Gensler

    (University of Münster)

  • Rolf Weiber

    (University of Trier)

  • Thomas Weiber

Abstract

In many problems in science and practice, the following questions arise: Which one of two or more alternative states is present or which event will occur? Which factors are suitable for the decision or prognosis and what influence do they have on the occurrence of a state or event? Often, only two alternative states or events are involved, as in the question whether a patient has a certain disease or not. Logistic regression can be used to answer such questions. The logistic regression is similar to discriminant analysis with regard to the problem definition. The main difference between the two methods is that logistic regression directly provides probabilities for the occurrence of the alternative states or the affiliations to the individual groups.

Suggested Citation

  • Klaus Backhaus & Bernd Erichson & Sonja Gensler & Rolf Weiber & Thomas Weiber, 2021. "Logistic Regression," Springer Books, in: Multivariate Analysis, chapter 0, pages 267-354, Springer.
    • Handle: RePEc:spr:sprchp:978-3-658-32589-3_5
    DOI: 10.1007/978-3-658-32589-3_5
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