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Linear and Logistic Regression

  • Yuelin Li
  • Jonathan Baron
Chapter
Part of the Use R! book series (USE R)

Abstract

This chapter covers linear and logistic regression modeling. The two primary functions used in this chapter are lm() and glm(). Functions that support lm() and glm() are also covered, such as summary() to print out model summary statistics and anova() to compare nested linear models.

Keywords

Logistic Regression Data Frame Color Grade Model Overfit Residual Standard Error 
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.

Copyright information

© Springer Science+Business Media, LLC 2012

Authors and Affiliations

  1. 1.Department of Psychiatry and Behavioral SciencesMemorial Sloan-Kettering Cancer CenterNew YorkUSA
  2. 2.Department of PsychologyUniversity of PennsylvaniaPhiladelphiaUSA

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