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From |
Padmakumar Sivadasan <pmathru2@illinois.edu> |

To |
statalist@hsphsun2.harvard.edu |

Subject |
st: Question on interpreting interactions in linear regression models |

Date |
Tue, 15 Dec 2009 09:49:46 -0600 |

Hello, This is a basic question about interpreting interactions in linear regression models that I hope someone would be able answer or guide me to a useful reference. I was reading a paper in which the authors are interested in studying whether the effect of a continuous variable (X) on a continuous outcome variable (Y) varies between two periods (P=0 and P=1). They test this using interactions with the following linear regression model Y=b1+b2X+b3P+b4XP They find that b2 is significantly different from zero, while b4 and (b2+b4) are not significantly different from zero. The authors conclude that X has an influence on Y in the first period (i.e. when P=0) because b2 is significant. Further, they state that the influence of X in the second period (i.e. when P=1) is given by (b2+b4) and this is not significantly different from zero, implying that X has no influence on Y in the second period. Thus, the effect of X on Y varies between the two periods. Is this interpretation of the authors correct? Does not the fact that the interaction coefficient (b4) is non-significant directly imply that there is no change in the effect of X between the two periods? Thanks Padmakumar * * For searches and help try: * http://www.stata.com/help.cgi?search * http://www.stata.com/support/statalist/faq * http://www.ats.ucla.edu/stat/stata/

**Follow-Ups**:**Re: st: Question on interpreting interactions in linear regression models***From:*Maarten buis <maartenbuis@yahoo.co.uk>

**Re: st: Question on interpreting interactions in linear regression models***From:*Charles Koss <hqtiger@gmail.com>

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