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!

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!

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.

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!