At 12:50 PM 8/9/2009, Nikolaos Pandis wrote:
I have the following model
y=a + b1x1 + b2x2
y and x2 are continuous
x1=categorical with 3 levels
You shouldn't include x1 as is. You should break it up into dummy
variables. e.g. if for x1, 1 = Catholic, 2 = Protestant, 3 = Others,
it makes no sense to treat it as continous.
I find a large difference in the p-values for the explanatory
variables between the interaction and no-interaction model.
I centered for the continuous variable x2 ((sum x2, gen cx2=x2-r(mean)).
I get similar p values for interaction and no-interaction models.
Question: How about the categorical explanatory variable? Is it
appropriate to center this variable also? Does it make any sense?
No. Again, it shouldn't be in there in the first place; and if you
did dichotomize it you still wouldn't center.
This handout goes over the advantages of centering and how to
interpret results:
http://www.nd.edu/~rwilliam/stats2/l53.pdf
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Richard Williams, Notre Dame Dept of Sociology
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EMAIL: Richard.A.Williams.5@ND.Edu
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