P-curve: a key to the file-drawer.
By Uri Simonsohn, Leif D. Nelson, Joseph P. Simmons. Journal of experimental psychology. General, 2014
1,406 citations recorded by the source corpus.
Subfields: Artificial Intelligence, Statistics and Probability
View Paper: https://www.semanticscholar.org/paper/96a872d9a7dbf7bf60501dbeac86315d6730d878
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
In Artificial Intelligence
- Cynthia Rudin
- Gary King
- Beau Coker
- Ralph Adolphs
- J. Brunner
- T. Stanley
- Constantine Sedikides
- John P. A. Ioannidis
In Statistics and Probability
- Hristos Doucouliagos
- T. Stanley
- Cynthia Rudin
- Joseph K. Goodman
- Evan Weingarten
- John P. A. Ioannidis
- Ralph Adolphs
- Gary King
Citations in the corpus
- p-Curve and Effect Size (2014, neutral): “01) than high significant p values (.04 < p < .05; Cumming, 2008; Hung, O’Neill, Bauer, & Kohne, 1997; Simonsohn et al., 2014; Wallis, 1942).”
- The Hedonic Character of Nostalgia: An Integrative Data Analysis (2020, methodology): “As a formal test for publication bias, we conducted a p-curve analysis (Simonsohn et al., 2014) of the nostalgia effects on “happy,” which supported the evidential value of the included experiments.”
- RCTs to Scale: Comprehensive Evidence from Two Nudge Units (2020, background): “Thaler and Sunstein (2008) define nudges as “choice architecture that alters people’s behavior in a predictable way without forbidding any options or significantly changing their economic incentives.”
- A Theory of Statistical Inference for Ensuring the Robustness of Scientific Results (2018, methodology): “Problems with Replication of Scientific Studies and Proposed Solutions The evidence for p-hacking primarily comes from two types of meta-analyses: replication studies and the distribution of p-values for a set of independent findings (or “p-curve”) (Simonsohn et al. 2014).”
- The Power of Bias in Economics Research (2017, methodology): “…to identify and accommodate potential publication and related reporting biases (Stanley, 2005, 2008; Ioannidis and Trikalinos, 2007; Stanley et al., 2010; Stanley and Doucouliagos, 2014) and others have proposed methods to detect and evaluate the extent of p-value hacking (Simonsohn et al., 2014).”