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From |
Maarten Buis <maartenlbuis@gmail.com> |

To |
statalist@hsphsun2.harvard.edu |

Subject |
Re: st: Interpretation of interaction term in nonlinear models |

Date |
Thu, 30 May 2013 17:26:33 +0200 |

It often helps to include the reference category for one of the categorical variables: M.L. Buis (2012) "Stata tip 106: With or without reference", The Stata Journal, 12(1), pp. 162-164. Hope this helps, Maarten On Thu, May 30, 2013 at 4:52 PM, Suryadipta Roy <sroy2138@gmail.com> wrote: > Dear Maarten and fellow Statalisters, > > I actually had a related question as to whether there might be a > similar (one-sentence) interpretation in case of a three-way > interaction between the same categorical variable, the continuous > variable with another categorical variable (0/1). Of course, I can and > have used -margins - with -marginsplot- to show how the interaction > effects differ in the presence of this categorical variable, but I was > wondering if I could get some help with an easier interpretation. The > coefficient of the three-way interaction term (standardized continuous > by categorical by categorical) in the fixed effects Poisson regression > with the -irr- option is 0.74 and in the probability metric form is > -0.21. Once again, thank you very much for the help! > > Sincerely, > Suryadipta. > > On Thu, May 30, 2013 at 7:53 AM, Suryadipta Roy <sroy2138@gmail.com> wrote: >> Maarten, >> This is very helpful, thank you very much! For some reason, I thought >> that the z_phd variable in your example is a categorical variable as >> well when I had previously read the thread. I guess that I would need >> to standardize my continuous variable for a similar interpretation. >> >> Sincerely, >> Suryadipta. >> >> On Thu, May 30, 2013 at 7:19 AM, Suryadipta Roy <sroy2138@gmail.com> wrote: >>> Dear Statalisters, >>> >>> I am studying the effect of an interaction between a categorical >>> variable (0/1) and a continuous variable (0-6) on the dependent >>> variable in a nonlinear model (using -xtpoisson-). The value of the >>> coefficient using the -irr- option is 0.90, while the size of the >>> interaction term in the probability metric form is, of course, -0.11 >>> (exp(-0.11) = 0.90). My basic question is, if it might be possible to >>> have a one-sentence interpretation of the value of the coefficient in >>> the multiplicative form (0.90), e.g. something in the lines of "the >>> effect of the categorical variable increases by a factor of 0.9 (i.e. >>> a 10% reduction of the dependent variable) due to an 1% increase in >>> the continuous variable"? Any suggestion in this regard will be highly >>> appreciated. >>> >>> Sincerely, >>> Suryadipta Roy. >>> * >>> * For searches and help try: >>> * http://www.stata.com/help.cgi?search >>> * http://www.stata.com/support/faqs/resources/statalist-faq/ >>> * http://www.ats.ucla.edu/stat/stata/ > * > * For searches and help try: > * http://www.stata.com/help.cgi?search > * http://www.stata.com/support/faqs/resources/statalist-faq/ > * http://www.ats.ucla.edu/stat/stata/ -- --------------------------------- Maarten L. Buis WZB Reichpietschufer 50 10785 Berlin Germany http://www.maartenbuis.nl --------------------------------- * * For searches and help try: * http://www.stata.com/help.cgi?search * http://www.stata.com/support/faqs/resources/statalist-faq/ * http://www.ats.ucla.edu/stat/stata/

**Follow-Ups**:**Re: st: Interpretation of interaction term in nonlinear models***From:*Suryadipta Roy <sroy2138@gmail.com>

**References**:**st: Interpretation of interaction term in nonlinear models***From:*Suryadipta Roy <sroy2138@gmail.com>

**Re: st: Interpretation of interaction term in nonlinear models***From:*Suryadipta Roy <sroy2138@gmail.com>

**Re: st: Interpretation of interaction term in nonlinear models***From:*Suryadipta Roy <sroy2138@gmail.com>

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