# Is there a model that can handled unbalanced repeated measures data with 1 OR 2 follow ups?

I want to identify predictors of a binary healthcare outcome in a purely observational study, and some of my participants have 1 recorded outcome timepoint, while others have 2 recorded outcome timepoints. I do not care about time at all and I am not interested in within-person variation - time is not part of the research question, there is no conceptual reason that outcome time (1st vs 2nd) would matter, and the distribution of outcome variable values does not vary by time. I just want to be able to use ALL of my observations to make a statement about what variables predict the outcome in general.

I thought I would use GEE (generalized estimating equations) but then I read that with GEE every individual in the study needs to have at least 2 timepoints, so if that's correct, GEE would not serve my purpose. My sample size is very small (N total=79, N with 2 follow ups=40) and my outcome is binary. I welcome general statistics/model type selection tips, or software-specific tips as well. I was going to use PROC GEE in SAS with weighting via a missingness model before I found out it couldn't handle having unpaired response observations. Any tips are much appreciated. Thank you.

• Please say more about what differs between the 2 timepoints when they are available. Is the binary outcome for an individual identical between the 2 time points? (It's not clear what you mean when you say the "distribution" is the same for the 2 times.) How many patients have the outcome? Are there predictor variables that are collected at both times whose values might differ between times? What specific hypothesis are you testing?
– EdM
Commented Aug 14, 2020 at 15:25
• I am not testing a specific hypothesis. It's an exploratory analysis for a purely observational study and I'm looking at which variables on a survey predict a positive drug test result for a prescribed medication (i.e., recent adherence). At the first time point, 49 of 63 had a positive result and at the second time point, 41 of 56 had a positive result [ignore my earlier N from the prior post, it was intentionally approximate]. The study was designed to collect a baseline survey, and a survey and drug test result at 3 months and 6 months.
– L.S.
Commented Aug 14, 2020 at 19:06
• However, a lot of people did their survey and drug tests at quite different times (~30% were >1 week apart at both time points), so the data does not support comparing survey and drug test data within person over time. For this reason, I wanted to use baseline survey data to predict later drug tests results. The only time-variant variable would be the outcome. Does this help make it more possible to make methods recommendations? I appreciate any more thoughts you can share. thanks.
– L.S.
Commented Aug 14, 2020 at 19:07