MethodsBrief Report Estimating Differences and Ratios in Median Times to EventRogawski, Elizabeth T.; Westreich, Daniel J.; Kang, Gagandeep; Ward, Honorine D.; Cole, Stephen R.Author Information From the aDepartment of Epidemiology, University of North Carolina at Chapel Hill, Chapel Hill, NC; bDivision of Gastrointestinal Sciences, Christian Medical College, Vellore, India; and cDivision of Geographic Medicine and Infectious Diseases, Tufts Medical Center, Boston, MA. Submitted 23 September 2015; accepted 21 July 2016. Supported by the National Institute of Allergy and Infectious Diseases at the National Institutes of Health [5-T32-AI070114-08 to ETR], and the Eunice Kennedy Shriver National Institute of Child Health & Human Development and the Office of the Director of the National Institutes of Health [DP2-HD084070 to DJW]. The parent studies providing data for the reported example were supported by the National Institute of Allergy and Infectious Diseases at the National Institutes of Health [5-R01-AI072222 to HDW]. DJW engages in occasional, ad hoc consulting on epidemiologic methods for NIH/NICHD—there is no overlap with the present work. The other authors have no conflicts of interest to report. Supplemental digital content is available through direct URL citations in the HTML and PDF versions of this article (www.epidem.com). Correspondence: Elizabeth T. Rogawski, University of Virginia, Carter Harrison Research Bldg MR-6, 345 Crispell Drive, Room 2520, P.O. Box 801379, Charlottesville, VA 22908. E-mail: [email protected]. Epidemiology: November 2016 - Volume 27 - Issue 6 - p 848-851 doi: 10.1097/EDE.0000000000000539 Buy SDC Metrics Abstract Time differences and time ratios are often more interpretable estimates of effect than hazard ratios for time-to-event data, especially for common outcomes. We developed a SAS macro for estimating time differences and time ratios between baseline-fixed binary exposure groups based on inverse probability-weighted Kaplan–Meier curves. The macro uses pooled logistic regression to calculate inverse probability of censoring and exposure weights, draws Kaplan–Meier curves based on the weighted data, and estimates the time difference and time ratio at a user-defined survival proportion. The macro also calculates the risk difference and risk ratio at a user-specified time. Confidence intervals are constructed by bootstrap. We provide an example assessing the effect of exclusive breastfeeding during diarrhea on the incidence of subsequent diarrhea in children followed from birth to 3 years in Vellore, India. The SAS macro provided here should facilitate the wider reporting of time differences and time ratios. Copyright © 2016 Wolters Kluwer Health, Inc. All rights reserved.