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UID:pretalx-sips2026-dc-VSWYKZ@pretalx.com
DTSTART;TZID=EST:20260609T133500
DTEND;TZID=EST:20260609T134000
DESCRIPTION:What does it mean to evaluate replicability? Is it merely deter
 mining whether results are consistent across studies? Much of the existing
  literature on replicability draws conclusions exclusively from the compar
 ison of study results. However\, replicability is a multifaceted concept t
 hat involves additional inferential dimensions. This paper introduces a un
 ified and coherent framework in which distinct but related notions of repl
 icability are formally defined and jointly embedded within a single infere
 ntial structure. We focus on a Bayesian hierarchical model\, and show how 
 a single replicability analysis can meaningfully address four complementar
 y replicability questions: replicability as traditionally defined in indep
 endent studies\; inference at the meta-analytic level implied by a common 
 generative model\; consistency between individual studies and the shared m
 eta-analytic structure\; consistency between an existing body of evidence 
 and a new study arising from the same generative model. We illustrate our 
 framework in mediation analysis applied to real psychological data.
DTSTAMP:20260524T192105Z
LOCATION:AUDITORIUM
SUMMARY:Rethinking Replicability: a Unified Bayesian Framework for Multiple
  Facets - Ester Alongi
URL:https://pretalx.com/sips2026-dc/talk/VSWYKZ/
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