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Publication Bias gathers books that explore how research with “positive” or striking results is more likely to be published, promoted, and cited than studies with null or contradictory findings. Titles in this category unpack the mechanisms behind selective reporting—file-drawer effects, p-hacking, and HARKing—and trace their consequences for evidence in medicine, psychology, economics, and beyond. Expect methodological guides to meta-analysis and preregistration, insider accounts of editorial and media incentives, case studies from the replication crisis, and proposals for reforms such as Registered Reports, open data, and trial registries. These books help readers understand how the research and publishing ecosystem shapes what we read as “the science,” and offer practical tools for evaluating claims and building more reliable knowledge.

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