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How to do Logistic Regression


Train in R

Predictive Analytics- The Book

Logistic regression is a widely used technique in database marketing for creating scoring models and in risk classification . It helps develop propensity to buy, and propensity to default scores (and even propensity to fraud ) .

This is more of a practical approach to make the model than a theory based approach.(I was never good at the theory ;) )

If you need to do Logistic Regression using SPSS, a very good tutorial ia available here


(Note -Copyright 1998, 2008 by G. David Garson.
Last update 5/21/08.)

For SAS a very good tutorial is here -

SAS Annotated Output
Ordered Logistic Regression. UCLA: Academic Technology Services, Statistical Consulting Group.

from http://www.ats.ucla.edu/stat/sas/output/sas_ologit_output.htm (accessed July 23, 2007).

For R the documentation (note :Still searching for R ‘s Logistic Regression ) is here

lrm(formula, data, subset, na.action=na.delete, method=”lrm.fit”, model=FALSE, x=FALSE, y=FALSE, linear.predictors=TRUE, se.fit=FALSE, penalty=0, penalty.matrix, tol=1e-7, strata.penalty=0, var.penalty=c(‘simple’,’sandwich’), weights, normwt, …)

For linear models in R -

An extremely good book if you want to work with R , and do not have time to learn it is to use the GUI
rattle and look at this book



  1. Domenic says:

    Informative article, exactly what I needed.

  2. Edith Ohri says:

    It can be useful to add a Prediction-versus-Actual graph

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