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 (September 2008, week 1)Back to main SAS-L pageJoin or leave SAS-L (or change settings)ReplyPost a new messageSearchProportional fontNon-proportional font
Date:         Tue, 2 Sep 2008 21:05:23 -0400
Reply-To:     Peter Flom <peterflomconsulting@mindspring.com>
Sender:       "SAS(r) Discussion" <SAS-L@LISTSERV.UGA.EDU>
From:         Peter Flom <peterflomconsulting@MINDSPRING.COM>
Subject:      Re: Class variables proc logistic
Comments: To: tal <talila.ar@GMAIL.COM>
Content-Type: text/plain; charset=UTF-8

tal <talila.ar@GMAIL.COM> wrote >I'm not sure- but i don't think the sampling is stratified. i have , >lets say:20 variables- "is XX important to you?" for each quest the >response is >1- important 2- not important 3-no answer. >(When i use the class statement- 3 dummy variables are created, but >I'm only interested in the first two- the third one is created >automatically- but i don't need it- and that's where I have a >problem) As i said , for each observation i want to count the number >of missing values in the questionnaire- and take it as explanatory >variable- but since a dummy variable is created for each var1-var20 >the number of missing values is a linear combination of these. > Does anybody know how to create only the 2 dummy variables that i >need in proc logistic, and drop the third one? >

If your IV has 3 levels, then LOGISTIC will create 2 dummy variables;, by default SAS uses EFFECT coding, and dummy (or reference) coding, is often better, but I don't think that explains your problem

So, could you show your code?

e.g

data today; length IV $4; input iv $ dv $ weight; datalines;; Imp yes 100 NotI yes 200 NA yes 50 Imp no 50 NotI no 100 NA no 50 ;;;;

proc logistic data = today; class iv (param = ref); model dv = iv; weight weight; run;

creates two dummy variables

Peter

Peter L. Flom, PhD Statistical Consultant www DOT peterflom DOT com


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