# P-Curve: A Key to the File Drawer

@article{Simonsohn2013PCurveAK, title={P-Curve: A Key to the File Drawer}, author={Uri Simonsohn and Leif D. Nelson and Joseph P. Simmons}, journal={Cognitive Linguistics: Cognition}, year={2013} }

Because scientists tend to report only studies (publication bias) or analyses (p-hacking) that "work," readers must ask, "Are these effects true, or do they merely reflect selective reporting?" We introduce p-curve as a way to answer this question. P-curve is the distribution of statistically significant p values for a set of studies (ps < .05). Because only true effects are expected to generate right-skewed p-curves-containing more low (.01s) than high (.04s) significant p values--only right…

## 1,134 Citations

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## References

SHOWING 1-10 OF 60 REFERENCES

### The file drawer problem and tolerance for null results

- Psychology
- 1979

Quantitative procedures for computing the tolerance for filed and future null results are reported and illustrated, and the implications are discussed.

### Inappropriate Fiddling with Statistical Analyses to Obtain a Desirable P-value: Tests to Detect its Presence in Published Literature

- PsychologyPloS one
- 2012

This article presents a method for detecting the presence of manipulation of statistical analyses to push a “near significant p-value” to a level that is considered significant in a distribution of p-values from independent studies.

### Publication decisions revisited: the effect of the outcome of statistical tests on the decision to p

- Economics
- 1995

Evidence that published results of scientific investigations are not a representative sample of results of all scientific studies is presented and practice leading to publication bias have not changed over a period of 30 years is indicated.

### A fail-safe N for effect size in meta-analysis.

- Environmental Science
- 1983

Rosenthan's (1979) concept of fail-safe N has thus far been applied to probability levels exclusively. This note introduces a fail-safe TV for effect size. Rosenthal's (1979) fail-safe N was an…

### A peculiar prevalence of p values just below .05

- PsychologyQuarterly journal of experimental psychology
- 2012

In null hypothesis significance testing (NHST), p values are judged relative to an arbitrary threshold for significance (.05). The present work examined whether that standard influences the…

### Replication and p Intervals: p Values Predict the Future Only Vaguely, but Confidence Intervals Do Much Better

- PsychologyPerspectives on psychological science : a journal of the Association for Psychological Science
- 2008

P is so unreliable and gives such dramatically vague information that it is a poor basis for inference that researchers should minimize the role of p by using confidence intervals and model-fitting techniques and by adopting meta-analytic thinking.

### Why Most Published Research Findings Are False

- BusinessPLoS medicine
- 2005

Simulations show that for most study designs and settings, it is more likely for a research claim to be false than true.

### Publication Decisions and their Possible Effects on Inferences Drawn from Tests of Significance—or Vice Versa

- Economics
- 1959

Abstract There is some evidence that in fields where statistical tests of significance are commonly used, research which yields nonsignificant results is not published. Such research being unknown to…

### Is the Replicability Crisis Overblown? Three Arguments Examined

- PsychologyPerspectives on psychological science : a journal of the Association for Psychological Science
- 2012

It is argued that there are no plausible concrete scenarios to back up such forecasts and that what is needed is not patience, but rather systematic reforms in scientific practice.

### Misleading funnel plot for detection of bias in meta-analysis.

- Psychology, BiologyJournal of clinical epidemiology
- 2000