When analysing binary outcomes, logistic regression is the analyst's default approach for regression modelling. The logit link used in logistic regression is the so called canonical link function for the binomial distribution. Estimates from logistic regression are odds ratios, which measure how each predictor is estimated to increase the odds of a positive outcome, holding the other predictors constant. However, most people find risk ratios easier to interpret than odds ratios. In randomized studies it is of course easy to estimate the risk ratio comparing the two treatment (intervention) groups. With observational data, where the exposure or treatment is not randomly allocated, estimating the risk ratio for the effect of the treatment is somewhat trickier.

Read moreEstimating risk ratios from observational data in Stata