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 (August 2010, week 1)Back to main SAS-L pageJoin or leave SAS-L (or change settings)ReplyPost a new messageSearchProportional fontNon-proportional font
Date:   Mon, 2 Aug 2010 17:50:31 -0500
Reply-To:   Andrew Agrimson <jagrimsasl@GMAIL.COM>
Sender:   "SAS(r) Discussion" <SAS-L@LISTSERV.UGA.EDU>
From:   Andrew Agrimson <jagrimsasl@GMAIL.COM>
Subject:   Re: Random Effects question
Comments:   To: Bhupinder Farmaha <bhupi80singh@yahoo.co.in>
In-Reply-To:   <000601cb328c$69942d80$3cbc8880$@co.in>
Content-Type:   text/plain; charset=ISO-8859-1

Hi Bhupinder,

Thanks for the response.

I think I understand somewhat. In you're first sentence you say that if you think there's is a random effect it should be specified. Can't the argument be made that there is always an subject specific random effect? If that's the case I guess my question is when is meaningful to specify it?

I not quite sure what you meant by "if the estimates of the parameters are big enough". Would you please clarify?

Thanks, Andy

On Mon, Aug 2, 2010 at 4:48 PM, Bhupinder Farmaha <bhupi80singh@yahoo.co.in>wrote:

> Hi Andy > > Based on my knowledge, if you have random components then specific it > otherwise they will get pooled into error terms. It might make your model > more complex but make sense if the estimates of the parameters are big > enough. Otherwise you can exclude that from the random statement. > > Does it make sense ? > Bhupinder > > -----Original Message----- > From: SAS(r) Discussion [mailto:SAS-L@LISTSERV.UGA.EDU] On Behalf Of > Andrew > Agrimson > Sent: Monday, August 02, 2010 4:41 PM > To: SAS-L@LISTSERV.UGA.EDU > Subject: Random Effects question > > Hello all, > > I have a question regarding random effects. > > Originally I was building a logistic regression model with multiple > observations per subject. To account for this I included a random intercept > term to induce correlation within subjects. My main focus though was the > fixed effects and the inclusion of the random intercept term was only to > account for the within subject correlation. > > I have recently decided to role up the observations to the subject level > and fit a binomial model instead. As I was preparing to do this I began to > wonder if including a random intercept in the binomial would still be > appropriate, i.e., most similiar to the random intercept logistic model. I > guess my thoughts are that a random intercept will induce the needed > correlation within subject, but it's also a bit more than that. It's also > going to estimate the unmeasured effects. It seems that this approach would > be similar to a frailty model in survival analysis. Is this appropriate > given that the main focus is on the fixed effects? Does anybody have any > thoughts on this? > > Thanks Andy > >


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