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From |
ZHVictor <victerzj2@hotmail.com> |

To |
"statalist@hsphsun2.harvard.edu" <statalist@hsphsun2.harvard.edu> |

Subject |
RE: st: question about the interaction term |

Date |
Thu, 25 Apr 2013 08:33:54 +0000 |

---------------------------------------- > Date: Thu, 25 Apr 2013 10:12:08 +0200 > Subject: Re: st: question about the interaction term > From: maartenlbuis@gmail.com > To: statalist@hsphsun2.harvard.edu > > On Thu, Apr 25, 2013 at 9:32 AM, ZHVictor wrote: > > So that means whenever I have the similar regression, I should use "test A+A*B=0" to double check, rather than only look at the interaction term. > > No, that is exactly opposite of what the main point of that article is. OK, I am thinking the basic idea of the paper is even the small and insignificant change can lead to a large change in significance level. Applying it to my example, it means even the interaction term is insignificant, the coefficient of A may be insignificant in B=1 case even thought it is significant in B=0 case. Thus, if I only look at the insignificant interaction term, I may conclude that the coefficient of A is still significant in B=1 case as in B=0 case. So it means even though the interaction term is insignificant, it may still be able to change the significance level of A. > > > Thus, for B=0 case, I should only look at the p-value of the coefficient of A to see whether the coefficient of A is significant. > > However, for B=1 case, I should actually test whether A+A*B is significant (use test A+A*B=0). If A+A*B is insignificant different from zero, I should say A has on effect on Y when B=1, even if the interaction term is insignificant. > > Is what my understanding correct? > > No, the trick is to work out exactly what the null hypothesis is that > you want to test and create a test that tests exactly that null > hypothesis. An interaction term measures exactly what an interaction > term measures and if that is what you want to know then that is > enough. For my case, I need to know two things. First, whether the coefficient of A is significant in B=0 case. Second, whether the coefficient of A is significant in B=1 case. Thus, for the B=0 case, it is easy to see the significance of A in the regression. However, for B=1 case, the coefficient of A becomes the coefficient of A+the coefficient of A*B. Therefore, I should test A+A*B=0. Right? > > > One more question is if the coefficient of A is -0.4 and the coefficient for the interaction is 0.2, so the coefficient of A in B=1 case should be -0.4+0.2=-0.2 but not -0.4+0=-0.4. Is that correct? > > I don't understand that question, where did the 0 come from? Since the interaction term is insignificant， I can treat it as 0. That is where the 0 comes from. > > -- Maarten > > --------------------------------- > 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/ * * 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: question about the interaction term***From:*Maarten Buis <maartenlbuis@gmail.com>

**References**:**st: question about the interaction term***From:*ZHVictor <victerzj2@hotmail.com>

**Re: st: question about the interaction term***From:*David Hoaglin <dchoaglin@gmail.com>

**RE: st: question about the interaction term***From:*ZHVictor <victerzj2@hotmail.com>

**Re: st: question about the interaction term***From:*Maarten Buis <maartenlbuis@gmail.com>

**RE: st: question about the interaction term***From:*ZHVictor <victerzj2@hotmail.com>

**Re: st: question about the interaction term***From:*Maarten Buis <maartenlbuis@gmail.com>

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