Date: Wed, 3 Oct 2007 11:18:45 -0300
Reply-To: Hector Maletta <firstname.lastname@example.org>
Sender: "SPSSX(r) Discussion" <SPSSX-L@LISTSERV.UGA.EDU>
From: Hector Maletta <email@example.com>
Subject: Re: Regression Analysis
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With regard to Bjorn's comment:
If gender is coded into two dummies the entire regression exercise
would be impossible due to perfect collinearity. Only one dummy should be
used, such as Male=1 and Female=0.
If regression is run in a stepwise fashion, SPSS may exclude any
variable (e.g. gender) because it is not a good predictor and thus fails to
fulfil the criteria for inclusion. Likewise, even if the variable is
included in the equation, an interaction involving that variable may be
Now, returning to the original Matt's message, apparently gender
was NOT excluded from the equation, even gender interaction terms. The
trouble is with the GRAPH involving that interaction. On that particular
issue I cannot give any light. My only comment is about the talk about
standardized and unstandardized coefficients. Unstandardized coefficients
would give the effect of being male (gender=1) relative to being female
(gender=0) if that is the way gender was coded (or the reverse if the
opposite is the case). Standardized coefficients would represent the effect
of each gender RELATIVE TO THE "AVERAGE GENDER", MEASURED IN STANDARD
DEVIATIONS. The average gender is the proportion of males in the sample, p,
and the standard deviation is the square root of p(1-p). This is a convolute
and totally dumb way of representing the effect of gender, in my humble and
possibly ignorant opinion. I would stick with the plain unstandardized
coefficients, telling me how the effect changes when people is male compared
with the effect when they are female.
From: SPSSX(r) Discussion [mailto:SPSSX-L@LISTSERV.UGA.EDU] On Behalf Of
Sent: 03 October 2007 10:31
Subject: Re: Regression Analysis
This may sound like a dumb question, but did you happen to make two
variables one for male (values 1 and 0) and one for female (values
))? Putting both of them in will cause problems, but I don't know
if it will
cause the problem you are talking about. For your regression you
use one variable for gender.
I only bring this possiblity up because one very simple mistake I
when people first run regression with recoded dummy variables is
place all of the dummy variables into the equation, when you need
at least one out.
On 10/2/07, Matt Donley <firstname.lastname@example.org> wrote:
> Hello all,
> My name is Matt, I am a third year psychology student at Monash
> in Melbourne, Australia.
> My group is conducting a research project into the relationship
> alcohol consumption and sex-related alcohol expectancies, with
> age as moderating factors. In order to obtain results, we are
> hierarchical multiple regression using SPSS v15.0 but have
> After centering relevant variables including age and recoding
> dummy variables (0,1) and performing interaction terms, we ran
> regression analysis.
> First level: sexual expectancies
> Second level: age and gender
> Third level: interaction terms
> We found significant results for enhancement (a sexual
> genderXenhancement. We are now calculating an interaction graph
> require unstandardised correlation coefficients but for some
> has excluded gender.
> Can anyone please suggest possible solutions as to how we would
> getting this data from the regression analysis? We have tried
> gender data as suggested by our tutor but we still do not get the
> need to produce the interaction graph. Any help would be greatly
> appreciated as we are really sturggling and running out of time
> have to hand it in.
> Thank-you in advance,
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