BEGIN:VCALENDAR PRODID:-//Columba Systems Ltd//NONSGML CPNG/SpringViewer/ICal Output/3.3- M3//EN VERSION:2.0 CALSCALE:GREGORIAN METHOD:PUBLISH BEGIN:VEVENT DTSTAMP:20220106T223505Z DTSTART:20220112T140000Z DTEND:20220112T150000Z SUMMARY:Aidan O'Keeffe - Regression discontinuity designs for time-to-ev ent outcomes: An approach using accelerated failure time models UID:{http://www.columbasystems.com/customers/uom/gpp/eventid/}zwm-ky2zmb1 p-llijx4 DESCRIPTION:Aidan O'Keeffe\, Associate Professor at the School of Mathema tical Sciences\, University of Nottingham is our speaker for the Statist ics seminar series.\n\nTitle: Regression discontinuity designs for time- to-event outcomes: An approach using accelerated failure time models\n\n Abstract: Regression discontinuity designs (RDDs) have been developed fo r the estimation of treatment effects using observational data\, where a treatment is administered using an externally defined decision rule lin ked to a continuous assignment variable. Typically\, RDDs have been appl ied to situations where the outcome of interest is continuous and non-te mporal. Conversely\, RDDs for time-to-event outcomes have received less attention\, despite such outcomes being common in many applications. \n\ nWe explore RDDs for a time-to-event outcome subject to right censoring. An accelerated failure time approach is used to establish a treatment e ffect estimate for a fuzzy RDD (where treatment is not always strictly a pplied according to the decision rule). This estimation approach is robu st to different levels of fuzziness and unobserved confounding\, assesse d using simulation studies and compares favourably to established struct ural accelerated failure time models. A brief example is presented in wh ich models are fitted to estimate the effect of metformin on mortality a nd cardiovascular disease rate using real observational data from UK Pri mary Care. STATUS:TENTATIVE TRANSP:TRANSPARENT CLASS:PUBLIC LOCATION:Zoom link: https://zoom.us/j/92947173491 END:VEVENT END:VCALENDAR