Modelling publication bias and p-hacking
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Publication bias and p-hacking are two well-known phenomena which strongly affect the scientific literature and cause severe problems in meta-analysis studies. Due to these phenomena, the assumptions are seriously violated and the results of the meta-analysis studies cannot be trusted. While publication bias is almost perfectly captured by the model of Hedges, p-hacking is much harder to model and no definitive solution has been found yet. In this paper we propose to model both publication bias and p-hacking with selection models. We derive some properties for these models, and we contrast them both formally and via simulations. Finally, two real data examples are used to show how the models work in practice.
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