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# Re: st: Interpretation of interaction term in log linear (non linear) model

 From Suryadipta Roy To statalist@hsphsun2.harvard.edu Subject Re: st: Interpretation of interaction term in log linear (non linear) model Date Wed, 12 Jun 2013 12:06:18 -0400

```Dear David,
I have used both log linear model (that apply only to country pairs
with nonzero bilateral imports) as well as fixed effects Poisson to
include the zero observations (based on some wonderful suggestions
from Bill Gould in Statablog here
http://blog.stata.com/2011/08/22/use-poisson-rather-than-regress-tell-a-friend/).
Earlier, Dimitriy had suggested an intuitive interpretation of the
coefficient terms in terms of semi-elasticity, and I can probably
persist with that interpretation for Poisson regression.

Best regards,

On Tue, Jun 11, 2013 at 7:57 PM, David Hoaglin <dchoaglin@gmail.com> wrote:
>
> Thank you for Stata Tip #87.  As Maarten explains in the last
> paragraph, the approach applies to all forms of multiplicative
> effects.  For your continuous dependent variable, you could work out
> interpretations along the lines of the odds ratios and odds in his
> example.  They would not, however, involve odds ratios (or
> incidence-rate ratios or hazard ratios).
>
> I don't recall that your earlier messages mentioned the many zeros.
> Your analysis should take that feature of the data into account.
> Perhaps the model should apply only to pairs of countries that have
> nonzero bilateral imports.
>
> Regards,
>
> David Hoaglin
>
> On Mon, Jun 10, 2013 at 1:48 PM, Suryadipta Roy <sroy2138@gmail.com> wrote:
>> Dear David,
>> The dependent variable in my regression is indeed a continuous
>> variable, highly skewed with a lot of zeros (bilateral imports between
>> countries). I will refrain from using an odds ratio interpretation as
>> you have suggested. Here is a link to Maarten's Stata tip # 87:
>> http://www.maartenbuis.nl/publications/interactions.pdf
>>
>> Best regards,
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```