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False-Positive Psychology
TLDR
It is shown that despite empirical psychologists’ nominal endorsement of a low rate of false-positive findings, flexibility in data collection, analysis, and reporting dramatically increases actual false- positive rates, and a simple, low-cost, and straightforwardly effective disclosure-based solution is suggested.
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P-Curve: A Key to the File Drawer
TLDR
By telling us whether the authors can rule out selective reporting as the sole explanation for a set of findings, p-curve offers a solution to the age-old inferential problems caused by file-drawers of failed studies and analyses.
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Algorithm aversion: people erroneously avoid algorithms after seeing them err.
TLDR
It is shown that people are especially averse to algorithmic forecasters after seeing them perform, even when they see them outperform a human forecaster, and this phenomenon, which is called algorithm aversion, is costly, and it is important to understand its causes.
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Data from Paper “False-Positive Psychology: Undisclosed Flexibility in Data Collection and Analysis Allows Presenting Anything as Significant”
The data includes measures collected for the two experiments reported in “False-Positive Psychology” [1] where listening to a randomly assigned song made people feel younger (Study 1) or actually be…
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Overcoming Algorithm Aversion: People Will Use Imperfect Algorithms If They Can (Even Slightly) Modify Them
TLDR
Giving participants the freedom to modify an imperfect algorithm made them feel more satisfied with the forecasting process, more likely to believe that the algorithm was superior, and morelikely to choose to use an algorithm to make subsequent forecasts.
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p-Curve and Effect Size
Journals tend to publish only statistically significant evidence, creating a scientific record that markedly overstates the size of effects. We provide a new tool that corrects for this bias without…
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Intuitive confidence: choosing between intuitive and nonintuitive alternatives.
TLDR
The authors found that decreasing intuitive confidence reduced or eliminated intuitive biases, indicating that intuitive biases are not inevitable but rather predictably determined by contextual variables that affect intuitive confidence.
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P-Curve and Effect Size: Correcting for Publication Bias Using Only Significant Results
Journals tend to publish only statistically significant evidence, creating a scientific record that markedly overstates the size of effects. We provide a new tool that corrects for this bias without…
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Better P-curves: Making P-curve analysis more robust to errors, fraud, and ambitious P-hacking, a Reply to Ulrich and Miller (2015).
TLDR
This work considers the possibility that researchers report only the smallest significant p value, the impact of more common problems, including p-curvers selecting the wrong p values, fake data, honest errors, and ambitiously p-hacked results, and provides practical solutions that substantially increase its robustness.
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The Effect of Accuracy Motivation on Anchoring and Adjustment: Do People Adjust from Provided Anchors?
TLDR
It is shown that although accuracy motivation fails to increase the gap between anchors and final estimates when people are uncertain about the direction of adjustment, accuracy motivation does increase anchor-estimate gaps whenPeople are certain about thedirection of adjustment.
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