Thanks Maarten and Jeff
I think it makes sense.
Anju
--- "Moore, Jeffrey E" <[email protected]> wrote:
> Yes, Maarten...you probably said it better than my
> explanation. Thanks.
> Hope these are helpful, Anju.
> Jeff
>
>
>
> -----Original Message-----
> From: [email protected]
> [mailto:[email protected]] On
> Behalf Of maartenbuis
> Sent: Thursday, February 24, 2005 3:21 PM
> To: [email protected]
> Subject: Re: st: Interaction term for dummy
> variables
>
> --- anju parthan <aparthan@y...> wrote:
> > However, I am concerned that if we calculate the
> > interaction terms by multiplying the two dummy
> coded
> > variables, in this case Male and BackPain, we are
> > combining some of the categories into the same
> group.
> >
> > For example,in the above sample
> >
> > ID=1 & Male*BackPain=0 represents male without
> back
> > pain, whereas
> > ID=3 & Male*BackPain=0 represents female with
> back
> > pain, and
> > ID=8 & Male*BackPain=0 represents female without
> back
> > pain.
>
> Dear Anju,
> An interaction term means that we think that the
> effect of one
> variable is different for different types of
> individuals, e.g. Males
> and Females. So if we think that Males react
> differently to backpain
> than females we would estimate the following model:
>
> Y = b0 + b1*backpain + b3*male*backpain + b2*male
>
> which can be rewritten as:
>
> Y = b0 + (b1 + b3*male)*backpain + b2*male
>
>
> Now the effect of backpain for females (male==0) is
> b1 + b3*0 = b1.
> The effect of backpain for males (male==1) is b1 +
> b3*1 = b1 + b3.
>
> So it is the COMBINATION of the variables backpain
> and male*backpain
> that ensures we are estimating both effects of
> backpain.
>
> Hope this helps,
> Maarten
>
>
>
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=====
____________________________________________________________
Anju Parthan,
Doctoral Candidate,
The University of Texas at Austin, PHAR-PHARMACY ADMIN
1 UNIVERSITY STATION A 1930, AUSTIN, TX-78712
Tel: (512) 459-4942; Fax: (512) 471-8762
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