Chapter 40 Further Reading: Critical Thinking About Attraction Research

Meta-Analysis and Forest Plots

Borenstein, M., Hedges, L. V., Higgins, J. P. T., & Rothstein, H. R. (2009). Introduction to meta-analysis. Wiley. The standard textbook for anyone wanting to understand meta-analysis in depth. Chapter 12 on heterogeneity and Chapter 30 on publication bias are particularly relevant.

Cumming, G. (2014). "The new statistics: Why and how." Psychological Science, 25, 7–29. An accessible argument for why effect sizes and confidence intervals should replace p-values as the primary currency of psychological research — directly relevant to the chapter's discussion of what we should take from statistical outputs.

P-Hacking, Pre-Registration, and Open Science

Simmons, J. P., Nelson, L. D., & Simonsohn, U. (2011). "False-positive psychology: Undisclosed flexibility in data collection and analysis allows presenting anything as significant." Psychological Science, 22, 1359–1366. The foundational paper on researcher degrees of freedom and p-hacking. Includes simulation results very similar to those in meta_analysis_tools.py. Open access available from the authors' websites.

Open Science Collaboration (2015). "Estimating the reproducibility of psychological science." Science, 349, aac4716. The landmark paper estimating that fewer than half of published social psychology findings replicate in independent samples. Still essential reading for understanding the scale of the replication crisis.

Chambers, C. D. (2017). The seven deadly sins of psychology: A manifesto for reforming the culture of scientific practice. Princeton University Press. An accessible, passionate account of how scientific incentive structures produce unreliable findings — and what the open science reform movement is doing about it.

Publication Bias

Egger, M., Smith, G. D., Schneider, M., & Minder, C. (1997). "Bias in meta-analysis detected by a simple, graphical test." BMJ, 315, 629–634. The original Egger's test paper. Freely available; methodologically accessible to non-specialists.

Science Communication and the Press Release Problem

Sumner, P., et al. (2014). "The association between exaggeration in health related science news and academic press releases: Retrospective observational study." BMJ, 349, g7015. Landmark study demonstrating that press release exaggeration predicts news exaggeration — and that researcher-approved press releases are less exaggerated than communications-office-only releases.

WEIRD Sampling and Generalizability

Henrich, J., Heine, S. J., & Norenzayan, A. (2010). "The weirdest people in the world?" Behavioral and Brain Sciences, 33, 61–83. The original WEIRD paper. Required reading for understanding sampling bias in behavioral science.