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Open AccessJournal ArticleDOI

False-Positive Psychology: Undisclosed Flexibility in Data Collection and Analysis Allows Presenting Anything as Significant

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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.
Abstract
In this article, we accomplish two things. First, we show that despite empirical psychologists' nominal endorsement of a low rate of false-positive findings (≤ .05), flexibility in data collection, analysis, and reporting dramatically increases actual false-positive rates. In many cases, a researcher is more likely to falsely find evidence that an effect exists than to correctly find evidence that it does not. We present computer simulations and a pair of actual experiments that demonstrate how unacceptably easy it is to accumulate (and report) statistically significant evidence for a false hypothesis. Second, we suggest a simple, low-cost, and straightforwardly effective disclosure-based solution to this problem. The solution involves six concrete requirements for authors and four guidelines for reviewers, all of which impose a minimal burden on the publication process.

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Statistical methods for linguistic research: Foundational Ideas—Part II

TL;DR: An informal introduction to the foundational ideas behind Bayesian data analysis, using a linear mixed models analysis of data from a typical psycholinguistics experiment, and some examples illustrating the flexibility of model specification in the Bayesian framework.
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A Common Neural Code for Perceived and Inferred Emotion

TL;DR: This research identifies neural patterns that correspond to emotions inferred from contextual information and finds that these patterns generalize across different cues from which an emotion can be attributed and provides a step toward understanding how the brain transforms stimulus-bound inputs into abstract representations of emotion.
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Specification curve analysis

TL;DR: In this article, the authors introduce specification curve analysis, which consists of three steps: identifying the set of theoretically justified, statistically valid and non-redundant specifications; displaying the results graphically, allowing readers to identify consequential specifications decisions; and conducting joint inference across all specifications.
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Conducting meta-analyses based on p values : Reservations and recommendations for applying p-uniform and p-curve

TL;DR: It is shown that in some situations, p-curve behaves erratically, whereas p-uniform may yield implausible estimates of negative effect size, which may result in overestimation of effect size under moderate-to-large heterogeneity and may yield unpredictable bias when researchers employ p-hacking.
References
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Journal ArticleDOI

The case for motivated reasoning.

TL;DR: It is proposed that motivation may affect reasoning through reliance on a biased set of cognitive processes--that is, strategies for accessing, constructing, and evaluating beliefs--that are considered most likely to yield the desired conclusion.

Why Most Published Research Findings Are False

TL;DR: In this paper, the authors discuss the implications of these problems for the conduct and interpretation of research and suggest that claimed research findings may often be simply accurate measures of the prevailing bias.
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Group sequential methods in the design and analysis of clinical trials

TL;DR: In this article, a group sequential design is proposed to divide patient entry into a number of equal-sized groups so that the decision to stop the trial or continue is based on repeated significance tests of the accumulated data after each group is evaluated.
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Measuring the Prevalence of Questionable Research Practices With Incentives for Truth Telling

TL;DR: It is found that the percentage of respondents who have engaged in questionable practices was surprisingly high, which suggests that some questionable practices may constitute the prevailing research norm.
Journal ArticleDOI

Attribution of success and failure revisited, or: The motivational bias is alive and well in attribution theory

TL;DR: The authors found that self-serving effects for both success and failure are obtained in most but not all experimental paradigms, and that these attributions are better understood in motivational than in information-processing terms.
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