2026-06-09 –, AUDITORIUM
What does it mean to evaluate replicability? Is it merely determining whether results are consistent across studies? Much of the existing literature on replicability draws conclusions exclusively from the comparison of study results. However, replicability is a multifaceted concept that involves additional inferential dimensions. This paper introduces a unified and coherent framework in which distinct but related notions of replicability are formally defined and jointly embedded within a single inferential structure. We focus on a Bayesian hierarchical model, and show how a single replicability analysis can meaningfully address four complementary replicability questions: replicability as traditionally defined in independent studies; inference at the meta-analytic level implied by a common generative model; consistency between individual studies and the shared meta-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.
Gianmarco Altoè (Department of Developmental Psychology and Socialisation, University of Padua, Padua, Italy) and Giovanni Parmigiani (Department of Data Science, Dana Farber Cancer Institute & Department of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, Massachusetts)
Could you give us a rough idea of what your lightning talk / poster presentation will cover? Such as:: A brief presentation of past research (a completed study), Pitching an idea
My name is Ester Alongi. I am pursuing a PhD in Statistical Science at the University of Padua, supervised by Gianmarco Altoè, Full Professor at the Department of Developmental Psychology and Socialisation, University of Padua. I am currently conducting a visiting period at Dana-Farber Cancer Institute in Boston under the supervision of Giovanni Parmigiani, Full Professor at the Department of Data Science, Dana-Farber Cancer Institute, and at the Department of Biostatistics, Harvard T.H. Chan School of Public Health. My research interests focus on Bayesian statistics and mediation analysis, particularly in applications to psychological research.