BEGIN:VCALENDAR
VERSION:2.0
PRODID:-//CERN//INDICO//EN
BEGIN:VEVENT
SUMMARY:Assessing replication success via skeptical mixture priors
DTSTART;VALUE=DATE-TIME:20230629T083000Z
DTEND;VALUE=DATE-TIME:20230629T085000Z
DTSTAMP;VALUE=DATE-TIME:20260909T193136Z
UID:indico-contribution-1014@cern.ch
DESCRIPTION:Speakers: Leonardo Egidi (Università degli Studi di Trieste)\
 nThere is a growing interest in the analysis of replication studies of ori
 ginal findings across many disciplines. When testing a hypothesis for an e
 ffect size\, two Bayesian approaches stand out for their principled use of
  the Bayes factor (BF)\, namely the replication BF (Verhagen and Wakenmale
 rs\, 2014) and the skeptical BF (Pawel and Held\, 2022). In both cases rep
 lication data are used to compare an "advocacy" prior against a benchmark.
  For the replication BF\, the latter is the standard point null hypothesis
  of no effect while for the skeptical BF it represents the prior of somebo
 dy who is unconvinced by the original findings. We propose a novel skeptic
 al mixture prior which incorporates skepticism and limits prior-data confl
 ict. We support our proposal with theoretical results on consistency of th
 e resulting BF\, we illustrate its features on an extended example\, and w
 e apply it to case studies from the Social Sciences Replication Project.\n
 \n**Keywords**: Bayes factor\, consistency\, prior-data conflict\,\nreplic
 ation studies.\n\n**References:**\n\nPawel\, S.\, & Held\, L. (2022). The 
 sceptical Bayes factor for the assessment of replication success. *Journal
  of the Royal Statistical Society Series B: Statistical Methodology*\, 84(
 3)\, 879-911.\n\nVerhagen\, J.\, & Wagenmakers\, E. J. (2014). Bayesian te
 sts to quantify the result of a replication attempt. *Journal of Experimen
 tal Psychology: General*\, 143(4)\, 1457.\n\nhttps://indico.unina.it/event
 /67/contributions/1014/
LOCATION:Department of Political Sciences Aula Spinelli
URL:https://indico.unina.it/event/67/contributions/1014/
END:VEVENT
END:VCALENDAR