Hi, I am trying to interpret the coefficients in the model: RateOfMotorPlay ~ TestNumber + Sex + TestNumber * Sex where there are thee different tests and Sex is (obviously) binary. My results are: Residuals: Min 1Q Median 3Q Max -86.90 -26.28 -7.68 22.52 123.74
Coefficients: Estimate Std. Error t value Pr(>|t|) (Intercept) 29.430 6.248 4.710 4.80e-06 *** TestNumber2 56.231 8.837 6.364 1.47e-09 *** TestNumber3 75.972 10.061 7.551 1.82e-12 *** SexM 7.101 9.845 0.721 0.472 TestNumber2:SexM -16.483 13.854 -1.190 0.236 TestNumber3:SexM -24.571 15.343 -1.601 0.111 --- Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1 Residual standard error: 40.97 on 188 degrees of freedom Multiple R-squared: 0.3288, Adjusted R-squared: 0.3109 F-statistic: 18.42 on 5 and 188 DF, p-value: 7.231e-15 I am looking for one number that will represent the significance of the interaction term. I was thinking of doing an F test comparing this model to one without the interaction. When I do this, I get a highly significant result. I am not exactly sure how to interpret this. In particular, it seems strange to me to have a significant interaction term without both independent variables being significant. Any advice would be highly appreciated. Thanks! -- View this message in context: http://r.789695.n4.nabble.com/Interpreting-coefficients-in-linear-models-with-interaction-terms-tp4655365.html Sent from the R help mailing list archive at Nabble.com. ______________________________________________ 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.