Thanjavur, I'm new to R, so it is possible I'm interpreting you syntax incorrectly, but it looks like in the second equation you are only including the interaction of age*race, the main effect of age, but not the main effect of race which is what came out significant in your first model.
In effect you have measured two different things and one of them is significant. In the first regression you have measured a general shift in the regression giving each racial group a different intercept. In the second, you are measuring whether there should be two different slopes for the line relating to age. One for european ages and one for non-european ages, which did not turn out to be significant. Based on the information you have presented you should not include the interaction, but should include the main effect for race. HOWEVER, as a general rule, you should include the main effects along with your test for interactions between them. age,race,age*race When you do this it is possible that the interaction will then also be significant. Hope that helps. Dave Tuesday, January 22, 2008, 11:20:01 AM, you wrote: TB> Hi, TB> I am trying a linear regression model where the dependent variable is the size of the heart corrected for the patient's height and weight. This is labelled as LAVI. The independent variables are TB> race (european or non-eurpoean), age, sex (male or female) of the patient and whether they have diabetes and high blood pressure. sample size 2000 patients selected from a community. TB> when I model TB> model1<-lm(lavi~age+sex+race+diabetes+hypertension, data=tb1) TB> and TB> model2<-lm(lavi~age+sex+age*race+diabetes+hypertension, data=tb1) TB> in the first model race comes out as a significant predictor (p<0.005) where as in the second model race is not a significant predictor of lavi (p=.076) TB> in my dataset mean age is 55.2 years in the non-europeans and 56.7 years in the europeans (p <0.0001 by t.test). TB> should I or should I not include the interaction (age*race) in the model. Is it an acceptable rule to put in interactions if there is a significant relation between the indepenedent variables in TB> univariate analyses. TB> Many thanks TB> bragadeesh TB> _________________________________________________________________ TB> Helping your favorite cause is as easy as instant messaging. You IM, we give. TB> [[alternative HTML version deleted]] -- Best regards, David Young mailto:[EMAIL PROTECTED] ______________________________________________ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.