Z-Curve
Definition: Computing a Z-score is a statistical approach mainly used to obtain the ‘Estimated Replication Rate’ (ERR) and ‘Expected Discovery Rate’ (EDR) for a set of reported studies. Calculating a z-curve for a set of statistically significant studies involves converting reported p-values to z-scores, fitting a finite mixture model to the distribution of z-scores, and estimating mean power based on the mixture model. The Z-curve analysis can be performed in R through a dedicated package - https://cran.r-project.org/web/packages/zcurve/index.html.
Related terms: Altmetrics, File drawer ratio, P-curve, P-hacking, Replication, Statistical power
References:
- Bartoš, F., & Schimmack, U. (2020). Z-Curve 2.0: Estimating replication rates and discovery rates. https://doi.org/10.31234/osf.io/urgtn
- Brunner, J., & Schimmack, U. (2020). Estimating population mean power under conditions of heterogeneity and selection for significance. Meta-Psychology, 4, MP.2018.874. https://doi.org/10.15626/MP.2018.874
Originally drafted by: Bradley J. Baker
Reviewed by: Kamil Izydorczak, Sam Parsons, Charlotte R. Pennington, Mirela Zaneva