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 2009, week 1)Back to main SAS-L pageJoin or leave SAS-L (or change settings)ReplyPost a new messageSearchProportional fontNon-proportional font
Date:         Sun, 4 Oct 2009 15:19:21 -0700
Reply-To:     j1een <jess.nagel@YAHOO.COM>
Sender:       "SAS(r) Discussion" <SAS-L@LISTSERV.UGA.EDU>
From:         j1een <jess.nagel@YAHOO.COM>
Organization: http://groups.google.com
Subject:      Re: Help with RBCD and SAS code
Comments: To: sas-l@uga.edu
Content-Type: text/plain; charset=ISO-8859-1

On Sep 28, 11:12 am, Warren.Schlec...@TPWD.STATE.TX.US (Warren Schlechte) wrote: > Although no expert, I will add my understanding as well. > > With a fixed effect, you are assuming the inference will only apply to > the set of objects sampled. With a random effect, you are assuming that > the set of objects investigated are a sample from a larger population. > Thus, you have a sample, and need to account for the fact that your > sample has variance, and that a sample can only tell you so much about > the larger population. Because of the narrower inference with the fixed > effect idea, you might see a treatment effect that is significant, but > when you broaden the inference space, your variance increases, meaning > your treatment effect may no longer be strong enough to be significant. > > Proc GLM assumes a narrow inference space (Fixed Effects); Proc MIXED > assumes a broad inference space, but narrower inference spaces can be > defined by reducing the number of random effects in the model. > > Warren Schlechte > > -----Original Message----- > From: Steve Denham [mailto:steve...@YAHOO.COM] > Sent: Monday, September 28, 2009 9:07 AM > Subject: Re: Help with RBCD and SAS code > > I would guess that GLM is giving significant results in the type 3 > table, but what do you find in the random section--particularly after > changing to: > > PROC glm data=dataset; > class block treatment; > model samplevar = block treatment block*treatment; > random block block*treatment/test; > run; > > You need the /test option on the random statment to test against the > "proper" mean square. > > By the way, the GLM documentation says this about random effects: > > Note:PROC GLM uses only the information pertaining to expected mean > squares when you specify the TEST option in the RANDOM statement and, > even then, only in the extra tests produced by the RANDOM statement. > Other features in the GLM procedure-including the results of the LSMEANS > and ESTIMATE statements-assume that all effects are fixed, so that all > tests and estimability checks for these statements are based on a > fixed-effects model, even when you use a RANDOM statement. Therefore, > you should use the MIXED procedure to compute tests involving these > features that take the random effects into account; see the section PROC > GLM versus PROC MIXED for Random-Effects Analysis and Chapter 56, The > MIXED Procedure, for more information. > > Steve Denham > Associate Director, Biostatistics > MPI Research, Inc. > > ----- Original Message ---- > From: j1een <jess.na...@YAHOO.COM> > To: SA...@LISTSERV.UGA.EDU > Sent: Saturday, September 26, 2009 7:50:09 PM > Subject: Help with RBCD and SAS code > > Hey all. > > I have a randomized complete block design for which I am trying to > decide on the correct Proc statement. In a nutshell, I have a block > (3 levels), treatment (4 levels), plot (3 reps within each treatment), > rep (2 within each plot) and samplevar. It's been a while since I've > used SAS. I assume that I can use either GLM or MIXED but when I > tried both, I received different output (i.e., glm outputs highly > significant treatment effect, mixed says no effect). In my design, > treatment is the only fixed variable. Here's the code: > > PROC glm data=dataset; > class block treatment; > model samplevar = block treatment block*treatment; > random block block*treatment; > run; > > OR.... > > PROC MIXED data=dataset; > class block treatment; > model samplevar = treatment; > random block block*treatment; > run; > > Anyone have any idea what I've done wrong? Again, my SAS knowledge is > rusty so I'd appreciate any help! Thanks!

Thanks everyone!


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