Z-Curve

Last updated on Nov 3, 2021

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: <a href='/glossary/altmetrics/'>Altmetrics</a>, File drawer ratio, <a href='/glossary/p-curve/'>P-curve</a>, <a href='/glossary/p-hacking/'>P-hacking</a>, Replication, <a href='/glossary/statistical-power/'>Statistical power</a>

References: Bartoš and Schimmack (2020), & Brunner and Schimmack (2020)

Drafted and Reviewed by: Bradley J. Baker, Kamil Izydorczak, Sam Parsons, Charlotte R. Pennington, Mirela Zaneva

Note that we are currently working on an automated mechanism to link references cited above with their full-length version that can be found at https://forrt.org/glossary/references with all references used so far.