FW: Re: Fwd: Re: Longitudinal logistic regression

[Weeks, Kyle]

The upcoming version of SPSS 15 will include Generalized Linear Models and Generalized Estimating Equations which will be able to handle, among other models, longitudinal logistic regression.  To see more of what is scheduled for SPSS 15 see http://www.spss.com/pdfs/S15CMPlr.pdf.

Regards.

Kyle Weeks, Ph.D.
Director of Product Management, SPSS Product Line
Product Management
SPSS Inc.
[hidden email]
www.spss.com
SPSS Inc. helps organizations turn data into insight through predictive analytics.

> -----Original Message-----
> From: SPSSX(r) Discussion [mailto:[hidden email]] On Behalf
> Of Dale Glaser
> Sent: Monday, July 17, 2006 10:25 PM
> To: [hidden email]
> Subject: Re: Fwd: Re: Longitudinal ogistic regression
>
> As far as I know SPSS is not equipped to handle, at least in the mixed
> model option, anything other than continuous outcomes...however, the
> HLM software has options for binomial/ordinal outcomes, with an option
> for the PQL estimator for the binary outcome......I may be wrong but I
> think MLwin uses the MQL estimator for binary/logistic
> models.........dale
>
> SR Millis <[hidden email]> wrote:  SR Millis wrote: Date: Mon, 17
> Jul
> 2006 14:27:31 -0700 (PDT)
> From: SR Millis
> Subject: Re: Longitudinal ogistic regression
> To: Gene Maguin
>
> If subjects have multiple observations over time time, standard
> logistic regression is inappropriate. There a many texts now available
> on longitudinal data analysis: Hedeker & Gibbons (2006), Weiss (2005),
> Brown & Prescott (1999), and Singer & Willett (2003), Verbeke &
> Molenberghs (2000), and Fitzmaurice, Laird, & Ware (2004)---among others.
>
> You need to use either a mixed effects regression model for binary or
> ordinal outcomes -- or generalized estimating equations (GEE) models.
>
> They can be easily implemented in SAS, Stata, or S-Plus----I don't
> know SPSS's capability in this regard.
>
> SR Millis
>
> Gene Maguin wrote:
> All,
>
> I am analyzing some longitudinal data with dichotomous or ordinal
> variables.
> I had thought to say
>
> LOGISTIC REGRESSION T2 WITH G T1/ENTER G T1/ENTER G BY T1.
>
> Or, for ordinal variables.
>
> PLUM T2 BY G WITH T1/LOCATION INTERCEPT G T1 G BY T1/PRINT FIT
> PARAMETER TPARALLEL.
>
> However, somebody here has commented that such analyses are incorrect
> but, off the top of his head, couldn't recall the cite. Can anyone
> comment and, if possible, give a cite. If this setup is incorrect,
> what are the alternatives?
>
> Thanks, Gene Maguin
>
>
>
> Scott R Millis, PhD, MEd, ABPP (CN & RP) Professor & Director of
> Research Department of Physical Medicine & Rehabilitation Wayne State
> University School of Medicine
> 261 Mack Blvd
> Detroit, MI 48201
> Email: [hidden email]
> Tel: [phone]
> Fax: [phone]
>
> *********************************************************
> This electronic message may contain information that is confidential
> and/or legally privileged. It is intended only for the use of the
> individual(s) and entity named as recipients in the message. If you
> are not an intended recipient of this message, please notify the
> sender immediately and delete the material from any computer. Do not
> deliver, distribute or copy this message, and do not disclose its
> contents or take any action in reliance on the information it contains. Thank you.
>
>
> Scott R Millis, PhD, MEd, ABPP (CN & RP) Professor & Director of
> Research Department of Physical Medicine & Rehabilitation Wayne State
> University School of Medicine
> 261 Mack Blvd
> Detroit, MI 48201
> Email: [hidden email]
> Tel: [phone]
> Fax: [phone]
>
> *********************************************************
> This electronic message may contain information that is confidential
> and/or legally privileged. It is intended only for the use of the
> individual(s) and entity named as recipients in the message. If you
> are not an intended recipient of this message, please notify the
> sender immediately and delete the material from any computer. Do not
> deliver, distribute or copy this message, and do not disclose its
> contents or take any action in reliance on the information it contains. Thank you.
>
>
>
> Dale Glaser, Ph.D.
> Principal--Glaser Consulting
> Lecturer--SDSU/USD/CSUSM/AIU
> 4003 Goldfinch St, Suite G
> San Diego, CA 92103
> phone: [phone]
> fax: [phone]
> email: [hidden email]
> website: www.glaserconsult.com