Firstly, thank you for taking the time to read my problem that I am having.
The goal: interpret the direction of the interaction term.
Variables: I have two continuous predictors (heart rate [HR] and pupil dilatation [PD]), predicting a dichotomous outcome (diagnosis of conduct disorder - no=0, yes=1)
I am controlling for age and gender.
Results: The interaction between HR and PD is significant, the beta is positive (suggesting a positive interaction - as HR increases so does PD). And my odds ratio is above 1 (3.1). I interpret the odds ratio meaning the increase in both HR and PD elevates the likelihood of being diagnosed with conduct disorder.
Here's the catch; I am not sure if I am looking at this correctly. I have been told that the positive interaction could indicate HR and PD are both negative resulting in a positive interaction also. How do I find out if the positive interaction means it is high HR and high PD or if it is low HR and low PD?
My closing thoughts are that the odds ratio may help explain this but I am not entirely sure if this is accurate. Another method I know may be plotting a simple slopes model but this is tricky because I have covariates.
I am open to suggestions, and would love to have some feedback on how to interpret this interaction term.
....................Estimate Std.
(Intercept):....-2.3594
age:..............0.2037
gender1:.......-1.8419*
HP:................-0.0324
BD:................1.4095*
HP:BD:...........1.1849*
..........................OR
(Intercept)..........0.0944774
age:...................1.2259709
gender:...............0.1585216
hp:.....................0.9681189
BD:....................4.0936999
HP:BD................3.032873
Many thanks in advance
The goal: interpret the direction of the interaction term.
Variables: I have two continuous predictors (heart rate [HR] and pupil dilatation [PD]), predicting a dichotomous outcome (diagnosis of conduct disorder - no=0, yes=1)
I am controlling for age and gender.
Results: The interaction between HR and PD is significant, the beta is positive (suggesting a positive interaction - as HR increases so does PD). And my odds ratio is above 1 (3.1). I interpret the odds ratio meaning the increase in both HR and PD elevates the likelihood of being diagnosed with conduct disorder.
Here's the catch; I am not sure if I am looking at this correctly. I have been told that the positive interaction could indicate HR and PD are both negative resulting in a positive interaction also. How do I find out if the positive interaction means it is high HR and high PD or if it is low HR and low PD?
My closing thoughts are that the odds ratio may help explain this but I am not entirely sure if this is accurate. Another method I know may be plotting a simple slopes model but this is tricky because I have covariates.
I am open to suggestions, and would love to have some feedback on how to interpret this interaction term.
....................Estimate Std.
(Intercept):....-2.3594
age:..............0.2037
gender1:.......-1.8419*
HP:................-0.0324
BD:................1.4095*
HP:BD:...........1.1849*
..........................OR
(Intercept)..........0.0944774
age:...................1.2259709
gender:...............0.1585216
hp:.....................0.9681189
BD:....................4.0936999
HP:BD................3.032873
Many thanks in advance