6
$\begingroup$

I'm planning an analysis that will require pooled logistic regression to analyze a longitudinal dataset with time-dependent explanatory variables (see here - D'Agostino, et al. 1990). However, the standard analysis uses regularly spaced intervals. My study has followup points at 0, 2, 6, 12, 24 months. What is a good way to model the effects of time given this structure of unevenly spaced intervals? Would a restricted cubic splines for the effects of time address the irregularity issue?

Thanks!

Improve this question
$\endgroup$

1 Answer 1

Reset to default
4
$\begingroup$

You can model the time trend in the log odds of the probability that $Y=1$ using a spline function (and using other methods). I do not believe that the time points need to be equally spaced, but rather that they be discrete and have roughly the same schedule for every subject.

Improve this answer
$\endgroup$

Your Answer

By clicking “Post Your Answer”, you agree to our terms of service and acknowledge you have read our privacy policy.

Not the answer you're looking for? Browse other questions tagged or ask your own question.