Systematically estimating ‘replicability’ by using Fear Conditioning Research as a case example (FEAR-REP)

• Applicant: Professorin Dr. Tina Barbara Lonsdorf
• Subject Area: Biological Psychology and Cognitive Neuroscience ; Personality Psychology, Clinical and Medical Psychology, Methodology
• Term: since 2022
• Project identifier: Deutsche Forschungsgemeinschaft (DFG) - Project number 501533638

The behavioral, social and cognitive sciences currently face an intense debate on the replicability of empirical findings. During the past years, the importance of methodological robustness as well as the abundance of measurement, processing and analytical heterogeneity has been highlighted and discussed - also in the field of fear conditioning research. Yet, a formal and comprehensive investigation on ‘replicability’ is lacking. The overarching aim of the FEAR-REP project is to systematically investigate ‘replicability’ from a meta-scientific perspective by using the field of fear conditioning research as a case example. The FEAR-REP project will systematically gauge insights into measurement challenges (reliability, convergent validity, risk for false positives, WP 1) for direct replication and generalizability through re-analyses across a large number of studies representing a diverse set of sample and procedural specifications. Furthermore, by employing the association between ‘negative emotionality’ and fear learning as a case example, the variation in effect sizes at different sample sizes will be systematically investigated (WP2). This will inform future sample size and power calculations by providing us with robust cross-study estimates. Finally, generalizability and robustness in light of data processing and analytical heterogeneity (in absence of formal theories) will be investigated though multiverse/specification curve analyses which is expected to advance cumulative science on the association between ‘negative emotionality’ and ‘fear learning’ and provide insights into the robustness of this association against procedural and analytical heterogeneity that will help to evaluate methodological “closeness” of replication and generalization attempts.

• DFG Programme: Research Grants