Date: Mon, 26 Feb 2007 14:20:44 -0500
Reply-To: Daniel Robertson <djr47@cornell.edu>
Sender: "SPSSX(r) Discussion" <SPSSX-L@LISTSERV.UGA.EDU>
From: Daniel Robertson <djr47@cornell.edu>
Subject: Re: multilevel generalized linear model
In-Reply-To: <PMEJJAHAJHJANCGEODHEGEPNCFAA.statisticsdoc@cox.net>
Content-Type: text/plain; charset=ISO-8859-1; format=flowed
Well, it depends on how the data are clustered. SPSS 15 includes
generalized estimating equations in the GENLIN procedure, which handles
observations clustered within subjects with a binary response variable
(e.g., repeated measures data). But there is currently no capacity in
SPSS for handling subjects clustered within groups w/ a binary RV. As
has been pointed out, HLM 6 does this quite well, and a 15-day tryout is
available for download from <estore.e-academy.com>.
Dan R.
Statisticsdoc wrote:
> Kutsal,
>
> To fit an HLM model to dependent variables that are binary, multinomial, or
> ordinal, you will need a package like HLM 6. SPSS 15 does not handle these
> types of multilevel models (though one may hope that the next version will).
>
> HTH,
>
> Stephen Brand
>
> For personalized and professional consultation in statistics and research
> design, visit
> www.statisticsdoc.com
>
>
> -----Original Message-----
> From: SPSSX(r) Discussion [mailto:SPSSX-L@LISTSERV.UGA.EDU]On Behalf Of
> Kutsal Yesilkagit
> Sent: Sunday, February 25, 2007 11:00 AM
> To: SPSSX-L@LISTSERV.UGA.EDU
> Subject: multilevel generalized linear model
>
>
> Hi
>
> Is it possible to execute a multilevel generalized linear model for binary
> response variables with a dataset that contains clustered data (at the
> base level)?
>
> As far as I can see this is only possible in software that is specialized
> for mlm (HLM, MLWIN etc).
>
> kind regards
>
> Kutsal Yesilkagit
> assistant professor
> Utrecht School of Governance
> University of Utrecht
> Netherlands
>
>
--
Daniel Robertson
Sr. Research and Planning Associate
Institutional Research and Planning
Cornell University
440 Day Hall, Ithaca NY 14853-2801
ph:607.255.9642 / irp.cornell.edu
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