Szucs and Ioannidis 2017 (cognitive neuroscience)

Note

To download only this data file: Szucs.rds (509 KB)

To download all BEAR datasets, click here.

Szucs and Ioannidis 2017 (cognitive neuroscience)

Reference: Szucs and Ioannidis (2017).

Research question: empirical assessment of published effect sizes, statistical significance, and power in cognitive neuroscience and psychology literature.

Data availability: the article and supporting data are available from PLOS Biology https://journals.plos.org/plosbiology/article?id=10.1371/journal.pbio.2000797

Data description and source: the source contains 26,841 text-mined t-test records from 3,801 papers in 18 journals (cognitive neuroscience, psychology, and medical). The processed dataset preserves all three fields; for BEAR main dataset we include only the cognitive neuroscience subset (since psychology and medical literature is well covered by other datasets in BEAR).

Notes: the extraction targeted t-test records reported in article text and did not mine tables.

Data processing: we followed our default procedure for deriving z-values from t-values.

Model of z-values

The fitted mixture model is shown over the empirical distribution of absolute z-values. The solid line is a mixture of half-normals, with selection. The dashed line shows the distribution without selection. If there are inequalities (e.g. studies reporting p < 0.05) the histogram resamples values from the appropriate set.

References

Szucs, Denes, and John P. A. Ioannidis. 2017. “Empirical Assessment of Published Effect Sizes and Power in the Recent Cognitive Neuroscience and Psychology Literature.” PLoS Biology 15 (3): e2000797. https://doi.org/10.1371/journal.pbio.2000797.