{"action":"opened","issue":{"url":"https://api.github.com/repos/statsmodels/statsmodels/issues/2215","labels_url":"https://api.github.com/repos/statsmodels/statsmodels/issues/2215/labels{/name}","comments_url":"https://api.github.com/repos/statsmodels/statsmodels/issues/2215/comments","events_url":"https://api.github.com/repos/statsmodels/statsmodels/issues/2215/events","html_url":"https://github.com/statsmodels/statsmodels/issues/2215","id":55952490,"number":2215,"title":"ENH: estimate risk ratio in binomial model","user":{"login":"josef-pkt","id":440735,"avatar_url":"https://avatars.githubusercontent.com/u/440735?v=3","gravatar_id":"","url":"https://api.github.com/users/josef-pkt","html_url":"https://github.com/josef-pkt","followers_url":"https://api.github.com/users/josef-pkt/followers","following_url":"https://api.github.com/users/josef-pkt/following{/other_user}","gists_url":"https://api.github.com/users/josef-pkt/gists{/gist_id}","starred_url":"https://api.github.com/users/josef-pkt/starred{/owner}{/repo}","subscriptions_url":"https://api.github.com/users/josef-pkt/subscriptions","organizations_url":"https://api.github.com/users/josef-pkt/orgs","repos_url":"https://api.github.com/users/josef-pkt/repos","events_url":"https://api.github.com/users/josef-pkt/events{/privacy}","received_events_url":"https://api.github.com/users/josef-pkt/received_events","type":"User","site_admin":false},"labels":[],"state":"open","locked":false,"assignee":null,"milestone":null,"comments":0,"created_at":"2015-01-29T20:30:19Z","updated_at":"2015-01-29T20:30:19Z","closed_at":null,"body":"based on the comments in #2208 \r\n\r\n`risk ratio` is a useful effects measure that is often used in medical, epidemiological studies, and I guess other areas.\r\n\r\nIt makes a good use, example and test case for several extensions on top of GLM or Logit, and there is a large literature for it.\r\n\r\n- eform: exponentiated parameters as in Stata, `rr` is eform in log-binomial model\r\n- predictive margins: average treatment effect, ATTreated, ATUntreated see Bender Kuss 2010  (NNT, EIN, NNE)\r\n- log-binomial model for out-of domain GLM/LEF as in #2208 \r\n- comparison of different models, e.g. Poisson with robust standard errors because of variance misspecification.\r\n\r\n\r\n\r\nBender Kuss 2010\r\nRalf Bender, Oliver Kuss, Methods to calculate relative risks, risk differences, and numbers needed to treat from logistic regression, Journal of Clinical Epidemiology, Volume 63, Issue 1, January 2010, Pages 7-8, ISSN 0895-4356, http://dx.doi.org/10.1016/j.jclinepi.2009.07.007.\r\n"}}