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Logistic Regression

Useful information regarding the Logistic Regression method

First, see the sub-page "Why Logistic vs. Linear Regression".

NIST gives cursory mention of logistic regression here (under the paragraph titled "Numerical Methods' Forte")

Good overviews on Logistic Regression and implementation, include some (not all) that use the R software package:

Related methods and concepts

Interpreting Odds Ratios in Logistic Regression

Software packages

Statistica GLZ module

SAS has several packages that will do logistic regression. 
  • proc CATMOD
  • proc GENMOD
  • proc LOGISTIC
  • (Firth)
  • other?

R has several packages as well:
  • stat:glm
  • Design:lrm
  • Hmisc
  • rms
  • logistf
  • elrm (exact methods for lrm)
  • Google search "Logistic Regression using R"
  • (there are others that don't come to mind as this entry is made ... will add later if useful)
  • General R note:  "plogis" has consequently been called the ‘inverse logit’.  Check out ?plogis

Many other packages as well (Minitab, S-Plus, etc. etc.)

Good references include

Other related references include

Forms of the response variable

  • single-trial syntax, is applicable to binary, ordinal, and nominal response data.
  • events/trials syntax, is restricted to the case of binary response data.