I would like to get a model to predict the dichotomous yes/no outcome (yes sleep disturbance/ no sleep disturbance) and then output that to a new dataset for each individual at each time point (is this possible?). There are many individuals that do not have all 4 time points and we would like to be able to include everyone. So far I have only been able to get the model to output means/probabilities and they are the same for each participant and each time point (or just for individuals with data at that time point). Any suggestions on what model/code I should be using? For example, if my data and model look like this: data sleep; input ID Months SleepDist; cards; 1 0 1 1 10 1 1 25 0 1 39 1 2 0 1 2 10 . 2 25 1 2 39 0 3 0 1 3 10 . 3 25 0 3 39 . 4 0 1 4 10 . 4 25 0 4 39 0 5 0 1 5 10 1 5 25 1 5 39 0 6 0 0 6 10 . 6 25 0 6 39 1 ; proc genmod data= sleepdata; class ID /missing; model SleepDist = Months / dist=bin expected; repeated subject=ID / type=un covb corrw; output out = try pred= pred; run; What I get: ID Months SleepDist Predicted Value 1 0 1 0.164 1 10 1 0.269 1 25 0 0.485 1 39 1 0.694 2 0 1 0.164 2 10 . 0.269 2 25 1 0.485 2 39 0 0.694 3 0 1 0.164 3 10 . 0.269 3 25 0 0.485 3 39 . 0.694 ... I would like: ID Months SleepDist Predicted Value 1 0 1 1 1 10 1 1 1 25 0 0 1 39 1 1 2 0 1 1 2 10 . 1 2 25 1 1 2 39 0 0 3 0 1 1 3 10 . 0 3 25 0 0 3 39 . 1 … Thanks!
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