1
$\begingroup$

Possible Duplicate:
Interpreting main effect and interaction

In a GLM, I had one categorical predictor and one covariate. To ensure the covariate was consistent across levels of my predictor I included an interaction term. This was non significant. Am I then justified in removing it from the model? My categorical predictor is non significant when it is included, but significant when it is removed.

Any help would be much appreciated.

| cite | improve this question | | | | |
$\endgroup$
  • $\begingroup$ Does any underlying theory predict the interaction ought to be there? $\endgroup$ – whuber♦ Jul 26 '12 at 0:13
  • $\begingroup$ Not that I am aware of. I included it only to test the assumption of homogeneity of regression slopes. $\endgroup$ – Heather Jul 26 '12 at 7:40
  • $\begingroup$ Then I'm sure your question is a duplicate of several closely related questions about regression, significance, and covariates, including (but not limited to) stats.stackexchange.com/questions/19891 and stats.stackexchange.com/questions/22680. For more, search our site. $\endgroup$ – whuber♦ Jul 26 '12 at 11:51