Date: Sat, 18 Sep 2010 17:45:49 -0700
Reply-To: Bruce Weaver <firstname.lastname@example.org>
Sender: "SPSSX(r) Discussion" <SPSSX-L@LISTSERV.UGA.EDU>
From: Bruce Weaver <email@example.com>
Subject: Re: Parameter Sig. vs Effect Sig. & Interaction
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Simon - firstname.lastname@example.org wrote:
> My analysis involves a Generalized Estimating Equation --- two binary IVs
> predicting a binary DV. Each binary IV is dummy coded 0-1.
> When I run my analyses, the "test of model effects" Wald chi-square
> statistic is exactly the same as the "parameter estimate" Wald chi-square
> statistic for each predictor. However, when I add an INTERACTION term to
> the model (i.e. I ask SPSS to add it in automatically), this is no longer
> the case. (The Wald statistic for the interaction term matches, but the
> statistics for the other parameter estimates don't match the test of model
> To date, I'm not really clear on why adding the interaction makes this
> happen. I would like to report parameter estimates (odds ratios), but the
> significance levels of the parameter estimates change depending on which
> group I select for the reference group! (Just to reiterate, this does not
> happen when there is no interaction term.)
> Is there a way I can code my data so that this does not occur?
> If there's not, what is the appropriate thing to report?
> --- snip ---
Bear in mind that when the product term is included in the model, the
parameters for the main effects are really giving you simple main effects .
Suppose your variables are called A and B. When A*B is also in the model,
the parameter for A gives you the effect of A when B is set to its reference
level; and the parameter for B gives you the effect of B when A is set to
its reference level. So if you change the reference levels, you'll see
different parameter estimates. The parameter estimate for the A*B product
is unaffected by what you choose as the reference categories.
"When all else fails, RTFM."
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