LISTSERV at the University of Georgia
Menubar Imagemap
Home Browse Manage Request Manuals Register
Previous messageNext messagePrevious in topicNext in topicPrevious by same authorNext by same authorPrevious page (October 2003, week 1)Back to main SAS-L pageJoin or leave SAS-L (or change settings)ReplyPost a new messageSearchProportional fontNon-proportional font
Date:         Sun, 5 Oct 2003 20:05:56 GMT
Reply-To:     julierog@ix.netcom.com
Sender:       "SAS(r) Discussion" <SAS-L@LISTSERV.UGA.EDU>
From:         Roger Lustig <trovato@VERIZON.NET>
Subject:      Re: proc logistic query
Content-Type: text/plain; charset=us-ascii; format=flowed

Dear Rob: Check out

http://ftp.sas.com/techsup/download/stat/jackboot.html

which contains macros that will do bootstrap & jackknife resampling for most regression procedures.

Best,

Roger

Rob Appleby wrote: > Hello I have what I am sure is a rather inane query relating to proc > logistic, specifically, how to create a resampling program/macro > involving a training and testing data set? Please find the program for > the train/test phases below, which appears to work fine. What I would > like to do now is reiterate the process (say 500 times) so that > essentially the the training sets are different each time (and > therefore the predicted probabilities inputted into the test phase) > and then obtain an overall summary of misclassification and various > other output statistics. > > The data set I am using is relatively small (n = 441) and I worry > about the spectrum of 'goodness of fit'and maximum likelihood results > I get each time I run the procedure. > Any suggestions and advice would be very much appreciated > Thanks for your time, > Rob > > DATA FItrain FItest; > SET Fraser2; > IF RANUNI(0) < = 1/2 then OUTPUT FItrain; > ELSE OUTPUT FItest; > RUN; > title 'Severe Incidents Model'; > proc logistic data = FItrain order = data outest = PARMS descending > simple ; > class Walking (ref = FIRST) TOD jmale (ref = > FIRST) admale (ref = FIRST) submale (ref = FIRST) season; > model absolute = season TOD Walking > admale submale jmale / rsq lackfit EXPB SELECTION = > FORWARD SLE = 0.20 SLS = 0.10 CTABLE; > output out=out1 p=p; > run; > proc logistic data = FItest order = data inest = PARMS descending > simple ; > class Walking (ref = FIRST) TOD jmale (ref = > FIRST) admale (ref = FIRST) submale (ref = FIRST) season; > model absolute = season TOD Walking > admale submale jmale / rsq lackfit maxiter = 0 > EXPB; > output out=out2 p=p; > run; > proc print data=out2;


Back to: Top of message | Previous page | Main SAS-L page