```Date: Thu, 4 Sep 2008 22:28:40 -0700 Reply-To: stringplayer_2@yahoo.com Sender: "SAS(r) Discussion" From: Dale McLerran Subject: Re: PROC MIXED - Estimated G matrix is not positive definite. In-Reply-To: <6843c444-ed2e-4c66-8dd7-e5c8f93adc67@z66g2000hsc.googlegroups.com> Content-Type: text/plain; charset=us-ascii --- On Thu, 9/4/08, Ryan wrote: > From: Ryan > Subject: PROC MIXED - Estimated G matrix is not positive definite. > To: SAS-L@LISTSERV.UGA.EDU > Date: Thursday, September 4, 2008, 2:04 PM > Hi, > > I'm getting the following message: "Estimated G > matrix is not positive > definite" when I run the following: > > proc mixed data=mydata; > class ID; > model Y= / s ; > random intercept / subject=ID; > run; > > ---------- > Does this occur when the within variability is much larger > than the > between variability? The whole point of this analysis is to > measure > the covariance parameter estimates (residual and > intercept). Is it > reasonable to just interpret the random intercept as being > 0? > > Thoughts? > > Ryan Ryan, The non positive definite G matrix here means that your variance estimate for the random subject effect is zero. If you were to fit a random effects model using method of moments (specifying METHOD=TYPE3 and changing your RANDOM statement to read just RANDOM ID; or simply using the GLM procedure with a RANDOM statement), then you would likely find that the between subjects variance component estimate using moment methods has a negative value. This all means that there is less variation between the subject means than would be expected given the within-subject (residual or error) variance. Let me note, too, that you could remove the constraint that the between-subject variance estimate should be non-negative. If you run the code proc mixed data=mydata nobound; class ID; model Y= / s ; random intercept / subject=ID; run; then even when using REML I would be willing to bet that you will observe that the between subjects variance component estimate is actually negative. With REML (and ML) estimation, the default behavior is to constrain the variance component estimates to be positive (as is required for a variance). Dale --------------------------------------- Dale McLerran Fred Hutchinson Cancer Research Center mailto: dmclerra@NO_SPAMfhcrc.org Ph: (206) 667-2926 Fax: (206) 667-5977 --------------------------------------- ```

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