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Part of the book series: Springer Texts in Statistics ((STS))

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Abstract

Logistic regression is a technique similar to multiple regression with the new feature that the predicted response is a probability. Logistic regression is appropriate in the often-encountered situation where we wish to model a dependent variable which is either

  • dichotomous: The dependent variable can assume only the two possible values 0 and 1 (often as a coding of a two-valued categorical variable such as Male/Female or Treatment/Control).

  • sample proportion: The dependent variable is a probability and hence confined to the interval (0, 1).

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© 2004 Springer Science+Business Media New York

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Heiberger, R.M., Holland, B. (2004). Logistic Regression. In: Statistical Analysis and Data Display. Springer Texts in Statistics. Springer, New York, NY. https://doi.org/10.1007/978-1-4757-4284-8_17

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  • DOI: https://doi.org/10.1007/978-1-4757-4284-8_17

  • Publisher Name: Springer, New York, NY

  • Print ISBN: 978-1-4419-2320-2

  • Online ISBN: 978-1-4757-4284-8

  • eBook Packages: Springer Book Archive

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