Publication bias is a central threat to the accumulation of scientific evidence and validity of meta-analysis. Addressing publication bias is essential, but how can researchers best do this?
In this session, Maximillian Maier (PhD researcher at UCL) will discuss Robust Bayesian Meta-Analysis (RoBMA), a new method to address publication bias. RoBMA uses Bayesian model-averaging to apply multiple models of the publication process to the data simultaneously and then allows the data to guide the inference to be based most strongly on those models that predicted the data best.
Maximillian will explain the RoBMA method in detail and show applications of RoBMA to different psychological theories and effects, including nudging, the identifiable victim effect, and construal level theory, to assess the evidence for these findings after publication bias is taken into account. He will also present the results from a working paper, which compares publication bias across different disciplines.
Date: 07/06/2023