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Date:         Fri, 30 Dec 2005 14:03:36 -0500
Sender:       "SAS(r) Discussion" <SAS-L@LISTSERV.UGA.EDU>
From:         Jay Weedon <jweedon@EARTHLINK.NET>
Subject:      Re: Using Sub in Random statement of Proc Mixed
Comments: To:
Content-Type: text/plain; charset=us-ascii

On 30 Dec 2005 09:15:22 -0800, "Hari" <> 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.


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