Date: Tue, 9 Sep 2008 15:57:16 -0400
Reply-To: Jon Bernard <jon563@gmail.com>
Sender: "SPSSX(r) Discussion" <SPSSX-L@LISTSERV.UGA.EDU>
From: Jon Bernard <jon563@gmail.com>
Subject: Re: Fw: Re: Logistic Regression - Threshold effect sizes?
In-Reply-To: <282107.24621.qm@web50908.mail.re2.yahoo.com>
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Thanks again Scott.
I tried this method and now have to make sense of the output. I entered one
ordinal covariate and one binary DV, selecting the option for contrasts as
you explained below.
The results give the following Exp(B)'s (all of them significant at p <
.001):
var1(1) = 2.704
var1(2) = 2.198
var1(3) = 1.649
var1(4) = 1.189
Could I interpret this as suggesting that the impact of a one-point positive
change in response to the item is greater when the baseline value is 1 than
when it is 2, 3, or 4?
Thank you,
Jon
On Fri, Sep 5, 2008 at 6:36 PM, SR Millis <srmillis@yahoo.com> wrote:
> Jon,
>
> If you're using SPSS binary logistic regression, enter your ordinal
> variable as a covariate. Then, click on the Categorical button. This will
> take you to a new window where you indicate which covariates are
> categorical. The Contrast should be "Indicator." Then run the analysis.
>
> If you're using Stata software, you use the xi option.
>
> Scott Millis
>
>
>
>
> --- On Fri, 9/5/08, Jon Bernard <jon563@gmail.com> wrote:
>
> > From: Jon Bernard <jon563@gmail.com>
> > Subject: Re: Fw: Re: Logistic Regression - Threshold effect sizes?
> > To: "SR Millis" <srmillis@yahoo.com>
> > Cc: SPSSX-L@listserv.uga.edu
> > Date: Friday, September 5, 2008, 6:24 PM
> > Thank you Scott. Would you recommend any resources for a
> > quick study on
> > this technique?
> >
> > Jon
> >
> > On Fri, Sep 5, 2008 at 6:18 PM, SR Millis
> > <srmillis@yahoo.com> wrote:
> >
> > > Jon,
> > >
> > > If you're uncomfortable treating your ordinal
> > variable
> > > as though it were interval, you can always "dummy
> > > code" the ordinal variable---such that the
> > 5-category
> > > variable become 4 separate variables---and direct
> > > comparisons can be made. This can work pretty well if
> > you
> > > don't have a lot of ordinal vairables and if
> > you're
> > > sample size is sufficiently large.
> > >
> > > Scott Millis
> > >
> > > > --- On Fri, 9/5/08, Justin Black
> > > > <justin.black@gmail.com> wrote:
> > > >
> > > > > From: Justin Black
> > <justin.black@gmail.com>
> > > > > Subject: Re: Logistic Regression - Threshold
> > effect
> > > > sizes?
> > > > > To: "SR Millis"
> > <srmillis@yahoo.com>
> > > > > Date: Friday, September 5, 2008, 6:13 PM
> > > > > Scott, thank you for following up.
> > > > >
> > > > > What's puzzling to me is the seemingly
> > omnibus
> > > > nature
> > > > > of the effect. So, I
> > > > > could say that a 1-point increase in IV1 is
> > associated
> > > > with
> > > > > a, e.g., 40%
> > > > > increase in the likelihood of the event
> > occurring.
> > > > But
> > > > > that assumes that a
> > > > > 1-point increase in the IV has the same
> > effect on the
> > > > DV
> > > > > regardless of the
> > > > > baseline level of the IV. I don't think
> > that
> > > > > assumption is accurate in
> > > > > these particular data.
> > > > >
> > > > > I really feel like I'm missing something
> > here,
> > > > just
> > > > > can't figure out what.
> > > > > A look back at Hosmer & Lemeshow
> > didn't help
> > > > any.
> > > > >
> > > > > Thank you,
> > > > >
> > > > > Jon
> > > > >
> > > > > On Fri, Sep 5, 2008 at 6:00 PM, SR Millis
> > > > > <srmillis@yahoo.com> wrote:
> > > > >
> > > > > > Jon,
> > > > > >
> > > > > > What is puzzling in the results?
> > > > > >
> > > > > > Have you examined the degree of
> > collinearity
> > > > among the
> > > > > > predictors/covariates?
> > > > > >
> > > > > >
> > > > > >
> > > > > > Scott R Millis, PhD, MEd, ABPP
> > (CN,CL,RP), CStat
> > > > > > Professor & Director of Research
> > > > > > Dept of Physical Medicine &
> > Rehabilitation
> > > > > > Wayne State University School of
> > Medicine
> > > > > > 261 Mack Blvd
> > > > > > Detroit, MI 48201
> > > > > > Email: smillis@med.wayne.edu
> > > > > > Tel: 313-993-8085
> > > > > > Fax: 313-966-7682
> > > > > >
> > > > > >
> > > > > > --- On Fri, 9/5/08, Jon Bernard
> > > > > <jon563@gmail.com> wrote:
> > > > > >
> > > > > > > From: Jon Bernard
> > <jon563@gmail.com>
> > > > > > > Subject: Logistic Regression -
> > Threshold
> > > > effect
> > > > > sizes?
> > > > > > > To: SPSSX-L@LISTSERV.UGA.EDU
> > > > > > > Date: Friday, September 5, 2008,
> > 5:42 PM
> > > > > > > Fellow SPSSers,
> > > > > > >
> > > > > > > I am struggling with a logistic
> > regression
> > > > issue
> > > > > and
> > > > > > > thought I'd put it out
> > > > > > > to the list for some clarity.
> > > > > > >
> > > > > > > The dependent variable of interest
> > is a
> > > > binary
> > > > > event (0 =
> > > > > > > Did not happen, 1
> > > > > > > = Did happen). The independent
> > variables of
> > > > > interest are
> > > > > > > ordinal
> > > > > > > attitudinal survey items, with
> > responses on
> > > > a
> > > > > 5-point scale
> > > > > > > (1 = Strongly
> > > > > > > Disagree, 5 = Strongly Agree). I
> > have been
> > > > using
> > > > > logistic
> > > > > > > regression for
> > > > > > > the analysis, but either I'm
> > missing
> > > > > something in the
> > > > > > > results output or I'm
> > > > > > > using the wrong statistical
> > technique. I
> > > > have an
> > > > > inkling
> > > > > > > that the intervals
> > > > > > > between categories of the
> > independent
> > > > variables
> > > > > are not all
> > > > > > > equal. In other
> > > > > > > words, I think that the impact on
> > the
> > > > dependent
> > > > > variable of
> > > > > > > an independent
> > > > > > > variable score of 3 vs. one of 2
> > is greater
> > > > than
> > > > > that of a
> > > > > > > score of 5 vs.
> > > > > > > one of 4. Is that clear? If so,
> > what would
> > > > you
> > > > > recommend
> > > > > > > in order to test
> > > > > > > that hypothesis? Is there a class
> > of
> > > > techniques
> > > > > designed
> > > > > > > particularly for
> > > > > > > this kind of test?
> > > > > > >
> > > > > > > Very many thanks in advance for
> > your
> > > > assistance
> > > > > with this
> > > > > > > matter.
> > > > > > >
> > > > > > > Kind regards,
> > > > > > >
> > > > > > > Jon
> > > > > > >
> > > > > > > =====================
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