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 (December 2005, week 5)Back to main SAS-L pageJoin or leave SAS-L (or change settings)ReplyPost a new messageSearchProportional fontNon-proportional font
Date:         Fri, 30 Dec 2005 14:03:36 -0500
Reply-To:     jweedon@earthlink.net
Sender:       "SAS(r) Discussion" <SAS-L@LISTSERV.UGA.EDU>
From:         Jay Weedon <jweedon@EARTHLINK.NET>
Organization: http://newsguy.com
Subject:      Re: Using Sub in Random statement of Proc Mixed
Comments: To: sas-l@uga.edu
Content-Type: text/plain; charset=us-ascii

On 30 Dec 2005 09:15:22 -0800, "Hari" <excel_hari@yahoo.com> wrote:

>(After banging my head for past 8 days Im trying this group again) > >I posted my above doubts to SAS tech support. > >My query was :- > >------------------------------------------------------------------------- > >Can you tell me as to whether every model which has predictors both in >Model and random statement can be written in 2 different ways (one >without subject and second with subject statement and both of the >methods being syntactically equivalent). For example consider the >following example which I have picked from SAS/STAT help (Proc Mixed - >Getting Started - Clustered Data Example) > >proc mixed; > class Family Gender; > model Height = Gender; > random Family Family*Gender; > run; > > >Can you please tell me as to whether the above code has an alternate >way of writing in which a subject statement is included (and it should >give same results as the above one)? > > >------------------------------------------------------------------------- > >I got the following response from SAS support:- > >------------------------------------------------------------------------- > >Hari, > >Briefly, if there is a common factor to the RANDOM effects you can >factor out that common factor as SUBJECT=effect. So in the code that >you provided: > >proc mixed; > class Family Gender; > model Height = Gender/ddfm=satterth; > random Family Family*Gender; > run; > >Family is a common factor so you can use the following equivalent >specification: > >proc mixed; > class Family Gender; > model Height = Gender/ddfm=satterth; > random intercept gender/subject=family; > run; > >You may want to consider using DDFM=SATTERTH as it has been my >experience the DDFM=CONTAINMENT which is the method used by your >programs can take longer than DDFM=SATTERTH. > >------------------------------------------------------------------------- > >I couldnt appreciate the logic of "factor out that common factor". 2 >issues with it:- > >a) In what sense does factoring work/apply? If I "factor out" family in >random statement then I should be left with --> Random 1 gender >/subject = family; >-- while we have random intercept >gender/subject=family; --> I cant understand as to how number 1 gets >replaced with intercept (I know having number 1 in random statement is >weird but cant understand the logic of factor )

1 makes perfect sense, because computationally an intercept is the regression coefficient attached to a predictor that always has value 1, e.g., in the model

E(Y) = b1*1 + b2*X

you can see that b1 is the expected value of Y when X=0, which is the definition of the intercept.

MIXED always includes a fixed intercept unless you dictate otherwise, so the 1 is in the model as a fixed effect whether you know it or not. Specifying an additional random intercept is the same as also entering 1 as a random effect.

>b) Is the logic of factoring out prevalant across many other procedures >in SAS , which entails one to write same model using 2 different >syntaxes? I mean do we have concept of "factoring out" in other procs >as well (the Proc might not have subject option as such but somewhat on >similar sense). If yes,please point me to the relevant documentation in >SAS regarding "factoring out"

The way the MIXED documentation phrases it is:

"...specifying a subject effect is equivalent to nesting all other effects in the RANDOM statement within the subject effect." In other words, each family has its own intercept & its own gender effect.

JW


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