I am interesting in building a propensity-score model in which there are three treatment groups. The three treatments are "equivalent," in that none is patently an "intervention" or "control" group - they're just three interventions. I scanned earlier Statalist posts, and while I was able to find small pieces of information on this topic, those pieces were not sufficient for me to visualize the entire process.
I am able, for example, to use -mlogit- and produce, for each subject, the probability of being in each of the three treatment groups -- but where do I go from there? It would be ideal to have a well-written, easily-accessed on-line tutorial that illustrates the running of a three-group propensity model from beginning to end.
Also, the three groups in my data set are of badly unbalanced size -- the respective numbers of cases in the three groups are about 250, 150, and 46. Would the small size of that last group make a propensity-score model impractical from the start?
Thank you.
I am able, for example, to use -mlogit- and produce, for each subject, the probability of being in each of the three treatment groups -- but where do I go from there? It would be ideal to have a well-written, easily-accessed on-line tutorial that illustrates the running of a three-group propensity model from beginning to end.
Also, the three groups in my data set are of badly unbalanced size -- the respective numbers of cases in the three groups are about 250, 150, and 46. Would the small size of that last group make a propensity-score model impractical from the start?
Thank you.
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