Both data sets are from intensive longitudinal studies in which individual participants were asked the same survey assessment questions repeatedly over a period of time. The repeated factor for both data sets represents time, and the first assessment/time point for each participant was set to 0. For the one whose code IS working (I'll call this Data Set 1), the time unit was days, and the range was 0 (i.e. the first day of the study/first assessment/time point) to 27. Some participants had missing days/time points. For the data set whose code is NOT working (I'll call this one Data Set 2), the repeated factor was also time, but the units were in minutes. They are also a lot more spread out and variable than in Data Set 1. For example, whereas Data Set 1 participants all had 27 days of the study (even if they missed a day or two here or there in between), the participants for Data Set 2 were prompted randomly throughout the course of the day (over a 6 day period) to fill out the survey assessment. Although all participants were prompted an equal number of times per day for assessments, the particular analysis that I am currently trying to do is using only a subset of time points from the study (e.g., only time points for which the participant reported a certain type of stressful event). So, for example, the second time point for one participant might have been 30 (i.e., 30 minutes after the first time point) whereas for another participant it might be 240 (i.e., 4 hours after the first time point) or even 1440 (i.e., a full day after the first time point). Dataset 1 & its code came from a book on working with intensive longitudinal data, so if one was going to work, I'm not surprised that it was that one! Thanks so much for your time and thoughts, Nastassia
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