Evidence map›Paper›PMID 29276574›Full record

ArticleSocial psychological and personality science2017

Too True to be Bad: When Sets of Studies With Significant and Nonsignificant Findings Are Probably True.

Daniël Lakens, Alexander J Etz

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Social psychological and personality science, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 31 papers, 4 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
31citing papers in PubMed, 4 pooled it
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

31 citing papers in PubMed, 4 syntheses or guidelines pooled it.

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  13. People with disagreeable personalities (selfish, combative, and manipulative) do not have an advantage in pursuing power at work.Proceedings of the National Academy of Sciences of the United States of America · 2020
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

2 authors.

Daniël LakensHuman Technology Interaction Group, Eindhoven University of Technology, Eindhoven, the Netherlands.
Alexander J EtzDepartment of Cognitive Sciences, University of California, Irvine, CA, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Psychology journals rarely publish nonsignificant results. At the same time, it is often very unlikely (or "too good to be true") that a set of studies yields exclusively significant results. Here, we use likelihood ratios to explain when sets of studies that contain a mix of significant and nonsignificant results are likely to be true or "too true to be bad." As we show, mixed results are not only likely to be observed in lines of research but also, when observed, often provide evidence for the alternative hypothesis, given reasonable levels of statistical power and an adequately controlled low Type 1 error rate. Researchers should feel comfortable submitting such lines of research with an internal meta-analysis for publication. A better understanding of probabilities, accompanied by more realistic expectations of what real sets of studies look like, might be an important step in mitigating publication bias in the scientific literature.

Indexed as

likelihoodspowerpublication biasstatistical inferences

Identifiers

PMID29276574
PMCPMC5734376

What OpenQuestion holds

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Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.