May the power be with you: are there highly powered studies in neuroscience, and how can we get more of them?

Power-up: A Reanalysis of 'Power Failure' in Neuroscience Using Mixture Modeling

(2017) Camilla L. Nord et al.   JOURNAL OF NEUROSCIENCE

Measurement error and the replication crisis

(2017) Eric Loken et al.   SCIENCE

Neuroadaptive Bayesian Optimization and Hypothesis Testing

(2017) Romy Lorenz et al.   TRENDS IN COGNITIVE SCIENCES

Empirical assessment of published effect sizes and power in the recent cognitive neuroscience and psychology literature

(2017) Denes Szucs et al.   PLOS BIOLOGY

Questionable science and reproducibility in electrical brain stimulation research

(2017) Martin E. Héroux et al.   PLoS One

How to get statistically significant effects in any ERP experiment (and why you shouldn't)

(2016) Steven J. Luck et al.   PSYCHOPHYSIOLOGY

Multilevel analysis quantifies variation in the experimental effect while optimizing power and preventing false positives

(2015) Emmeke Aarts et al.   BMC NEUROSCIENCE

Power failure: why small sample size undermines the reliability of neuroscience

(2013) Katherine S. Button et al.   NATURE REVIEWS NEUROSCIENCE

Systematic Review of the Empirical Evidence of Study Publication Bias and Outcome Reporting Bias

(2008) Kerry Dwan et al.   PLoS One