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Re: st: Count data interaction terms

From   Maarten Buis <[email protected]>
To   [email protected]
Subject   Re: st: Count data interaction terms
Date   Tue, 23 Aug 2011 11:20:14 +0200

On Mon, Aug 22, 2011 at 5:50 PM, DA Gibson wrote:
> Im running an investigation into how unhealthy lifestyles (obestiy,
> smoking etc) effect health service usage and ideally id like to use a
> count analysis to do this. However im not sure whether as with OLS
> analyses you can include interaction terms e.g. y = B0
> +B1(X1)+B2(X2)+B3(X1*X2) where X1 and X2 are binary variables. Is this
> possible using count data?

Yes, the tricky part is interpretation, but that is not a big deal as
long as you interpret the incidence rate ratios rather than marginal
effects. Consider the example below. The baseline tells you that a
visitor to the park without camper, who visited the park alone and has
no kid with him/her is expected to catch .39 fish per visit(*). An
extra person added to the group increases that rate by a factor 3.07,
i.e. (3.07-1)*100%=207 % (the main effect of person). If this extra
person happens to a child, this effect of number of persons decreases
by a factor .78, i.e. -22%.

*------------------ begin example -----------------
webuse fish, clear
gen byte baseline = 1
poisson count i.camper c.persons##c.child baseline, ///
        irr nocons
*----------------- end example --------------------
(For more on examples I sent to the Statalist see: )

Also see: M.L. Buis (2010) "Stata tip 87: Interpretation of
interactions in non-linear models", The Stata Journal, 10(2), pp.

Hope this helps,

(*) I still have Stata 11, so I need this trick with a "variable"
baseline which is secretly a constant. I understand that in Stata 12
the display of the baseline rates, odds, hazards, etc. are no longer
suppressed, so there this trick is no longer necessary.

Maarten L. Buis
Institut fuer Soziologie
Universitaet Tuebingen
Wilhelmstrasse 36
72074 Tuebingen
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