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I am trying to perform logistic regression on data that contains a binary outcome. However, I do not have access to the outcome data.

I've calculated probabilities of a "1" outcome for each subject by assigning "risk points" to certain values of each variable and adding them up for each subject, so that the probability of a "1" is (sum of subject's risk points) / (total number of possible risk points). I then took the log of the odds ratio to calculate the logit, so I have a list of logit values between -3 and 2 for each subject.

However, I would like to use logistic regression to evaluate which variables have the greatest effect on the outcome probabilities. Is there a way in R to perform logistic regression using only the predictive variables and logit, without the binary outcome data? I have tried using glm and it does not work, because in order to do logisitic regression you need binary outcome data.

Thank you!

Emma
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  • Logistic regression requires binary outcome data - that's how logistic regression works. If you want to analyze non-binary outcome data, you need a different kind of regression. – A. S. K. Jun 08 '20 at 17:56
  • If I understand correctly, you want to analyze the probabilities that you've computed yourself; is that right? If so, do you want to do this to understand those probabilities better, or just as a placeholder analysis while you're waiting for real data? If it's the former, I'm puzzled, because you already know what variables affect those probabilities (you created them yourself!). – A. S. K. Jun 08 '20 at 17:58

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