I also tend to agree with Venita, although I also disagree with her in this particular case, for the reasons which Dale and others (e.g., may need PROC MIXED, or NLMIXED, or (at least) GENMOD bcs. of the problems they mention).

But I can't remember a post of Dale's I've disagreed with, and was wondering why he has quit using GLM even where it is appropriate. As Venita notes, the syntax for GLM is simpler than that for MIXED, NLMIXED, or GENMOD. I know there are lots of cases where GLM is NOT the right proc, but is there some reason not to use it when it IS the right PROC?

Peter

Peter L. Flom, PhD Assistant Director, Statistics and Data Analysis Core Center for Drug Use and HIV Research National Development and Research Institutes 71 W. 23rd St www.peterflom.com New York, NY 10010 (212) 845-4485 (voice) (917) 438-0894 (fax)

>>> Dale McLerran <stringplayer_2@YAHOO.COM> 1/22/2004 6:07:40 PM >>> In general, I agree with the comments Venita posts to SAS-L. In this particular case, I have to respectfully disagree. I have essentially quit use of PROC GLM in favor of either GENMOD or MIXED for normally distributed responses. In fact, it is the procedure MIXED which I advocate for >95% of problems where the response is normally distributed. Actually, I should throw the procedure NLMIXED in here as well. It is able to handle some problems that the MIXED procedure cannot deal with, although I would have to say that none of the problems which would require NLMIXED over the procedure MIXED are of the simple normally distributed response variety.

Dale

--- "DePuy, Venita" <depuy001@DCRI.DUKE.EDU> wrote: > Have you considered Proc GLM? > I think it's easier to comprehend than Genmod (at least to me) and it > will > handle the Repeated option. > Just a quick thought. > -Venita > > > ---------- > > From: Cacialli, Doug[SMTP:Doug_Cacialli@URMC.ROCHESTER.EDU]

> > Reply To: Cacialli, Doug > > Sent: Thursday, January 22, 2004 5:21 PM > > To: SAS-L@LISTSERV.UGA.EDU > > Subject: Appropraiteness of PROC GENMOD > > > > Y'all, > > > > I'd like to open with an apology for my statistical ignorance here > ... I'm > > not extremely savvy with complex analyses. I'm needing to do some > > regression analyses on the effects of five independent variables, > four of > > which are continuous and one of which is categorical, on number of > > episodes > > of a given disorder (which is obviously continuous). > > > > My first instinct was to run PROC LOGISTIC on account of the > categorical > > independent variable, but as the dependent variable isn't > categorical, I'm > > under the impression that PROC LOGISTIC would be inappropriate. > I've been > > using PROC GENMOD lately with the assistance of a consultant with > much > > more > > training than I, and it occurred to me that a generalized linear > model > > might > > work here. I threw this together: > > > > proc genmod data = work.ANALYSIS_I; > > class FAMILY_ID SEX; > > model N_EPISODES = ONSETAGE_MDD ONSETAGE_FIRST SEX > AGE_AT_T1; > > repeated subject = FAMILY_ID/corr=cs corrw; > > run; > > > > The repeated subject = FAMILY_ID takes the relation between certain > > subjects > > (these data were originally collected as part of a longitudinal > family > > study). > > > > My question, in short, is if this is a legit use of PROC GENMOD. > And if > > it's not, can someone suggest an appropriate tool? > > > > I've received a bit of help on a number of different issues from > SAS-L > > lately. Thank you all for your help, past and present. I'm > learning so > > much ... it's greatly appreciated. > > > > Doug out. > > > > ------------------------------------------- > > Doug Cacialli - Data Manager / Data Analyst > > Depression Research Laboratory > > University of Rochester Medical Center > > 300 Crittenden Boulevard - Box PSYCH > > Rochester, New York 14642 > > Phone: (585)273-3309 Fax: (585)506-0287 > > ------------------------------------------- > >

===== --------------------------------------- Dale McLerran Fred Hutchinson Cancer Research Center mailto: dmclerra@fhcrc.org Ph: (206) 667-2926 Fax: (206) 667-5977 ---------------------------------------

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