As a preface, I had been taught to assess the interaction term prior to higher end analyses. Figuring out whether or not you have to stratify your analysis early on is essential to saving time in the long run.
I am in the process of finalizing a manuscript (which has taken about a year to synthesize) and have been asked by my one of my co-authors if I evaluated an interaction term for a series of ordinal logistic regression models. Proportional odds assumption is valid, and my exposure is continuous. My dilemma exists in that I HAD evaluated the interaction term during my initial model building phases and it came up non-significant (p = 0.384).
eqn: y = B(group)+ B(exposure) + B(group*exposure) + baselinelogit)
However, since it had been so long since I did this, to satisfy their curiosity, I added the interaction to the full model after model building was long completed and it was statistically significant (p = 0.056).
eqn: y = B(group) + B(exposure) + B(group*exposure) + B(age) + B(followup_time) + baselinelogit)
I am a bit befuddled as to whether or not I should report the interaction term as significant now.
I only have about 360 observations in my dataset, but with only 5 terms, I doubt I'm overspecifiying the model. In addition, after stratifying by group, there is an independent association between the exposure and the outcome in one group but not the other.
I hope I was descriptive enough. Thanks in advance for any help you can offer.
I am in the process of finalizing a manuscript (which has taken about a year to synthesize) and have been asked by my one of my co-authors if I evaluated an interaction term for a series of ordinal logistic regression models. Proportional odds assumption is valid, and my exposure is continuous. My dilemma exists in that I HAD evaluated the interaction term during my initial model building phases and it came up non-significant (p = 0.384).
eqn: y = B(group)+ B(exposure) + B(group*exposure) + baselinelogit)
However, since it had been so long since I did this, to satisfy their curiosity, I added the interaction to the full model after model building was long completed and it was statistically significant (p = 0.056).
eqn: y = B(group) + B(exposure) + B(group*exposure) + B(age) + B(followup_time) + baselinelogit)
I am a bit befuddled as to whether or not I should report the interaction term as significant now.
I only have about 360 observations in my dataset, but with only 5 terms, I doubt I'm overspecifiying the model. In addition, after stratifying by group, there is an independent association between the exposure and the outcome in one group but not the other.
I hope I was descriptive enough. Thanks in advance for any help you can offer.