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Having carried out the regression below, I'm struggling to determine what the correct interpretation of the predictor variable would be.

Given that the dependent variable is binary, where 1=receiving a medicine and 0= not receiving a medicine. And the predictor variable is a measure of distance measured in km from a hospital.

Would the correct interpretation be that a 1km increase in distance from the hospital leads to a 2.26 percentage-point increase in the probability of receiving the medicine?

OR, a 1km increase in distance from the hospital leads to a 2.26% increase in the probability of receiving the medicine?

I'm trying to understand the difference between the two interpretations and which would be correct wrt to the regression?

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  • $\begingroup$ Did you perform normal regression or logistic regression? If the output is binary, a normal regression is not the correct tool to use. $\endgroup$ – Davide ND Jan 7 at 12:56
  • $\begingroup$ The regression was in fact the First stage of a Two Stage Least-Square computation. Even in that case would I have had to use another type of regression? $\endgroup$ – SoniaG Jan 7 at 13:10
  • $\begingroup$ I dont know what you mean by two stage computation. However, if the predicted value is binary then you should you a Logit or a Probit regression - which predict the probabilty instead of the value. $\endgroup$ – Davide ND Jan 7 at 13:29
  • $\begingroup$ If you're using 2SLS, what are your true variables? You can do 2SLS with binary outcomes, but I believe the predictors must also be binary. Were you told to use 2SLS here? Also, 0.226261 would be 22.61%. $\endgroup$ – Todd Burus Jan 7 at 13:31
  • $\begingroup$ Drawing a graph would help you think about this. $\endgroup$ – Nick Cox Jan 7 at 13:46

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