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I have a problem at hand which I'd think is fairly common amongst groups were R is being adopted for Analytics in place of SAS. Users would like to obtain results for logistic regression in R that they have become accustomed to in SAS.

Towards this end, I was able to propose the Design package in R which contains many functions to extract the various metrics that SAS reports.

If you have suggestions pertaining to other packages, or sample code that replicates some of the SAS outputs for logistic regression, I would be glad to hear of them.

Some of the requirements are:

  • Stepwise variable selection for logistic regression

  • Choose base level for factor variables

  • The Hosmer-Lemeshow statistic

  • concordant and discordant

  • Tau C statistic

Thank you for your suggestions.

harshsinghal
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    The rms package is the current successor to Design. And don't go posting on rhelp for problems with stepwise variable selection. Frank Harrell, the author of both Design and rms (as well as the original author of Proc LOGIST) is a very severe critic of stepwise methods. – IRTFM Jan 21 '11 at 05:18

2 Answers2

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Just because SAS does it, doesn't necessarily mean it's good statistical practice. Step-wise regression is particularly problematic.

hadley
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What I have found so far is that the Design and rms package to be the best (and only) package for these outputs.

Alison
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