ArticlePloS one2023
Hedges, mottes, and baileys: Causally ambiguous statistical language can increase perceived study quality and policy relevance.
Article in PloS one, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
What it found
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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.
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Who cites it
4 citing papers in PubMed.
- Opportunities and pitfalls of data contextualization in neuroimaging.Nature reviews. Neuroscience · 2026Review
- Causal inference on human behaviour.Nature human behaviour · 2024Review
- Causal and Associational Language in Observational Health Research: A Systematic Evaluation.American journal of epidemiology · 2022Article
- Avoidance of causality outside experiments: Hypotheses from cognitive dissonance reduction.Science progressArticle
Corrections and comments
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Authors and funding
7 authors.
Funding
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Abstract
There is a norm in psychology to use causally ambiguous statistical language, rather than straightforward causal language, when describing methods and results of nonexperimental studies. However, causally ambiguous language may inhibit a critical examination of the study's causal assumptions and lead to a greater acceptance of policy recommendations that rely on causal interpretations of nonexperimental findings. In a preregistered experiment, 142 psychology faculty, postdocs, and doctoral students (54% female), ages 22-67 (M = 33.20, SD = 8.96), rated the design and analysis from hypothetical studies with causally ambiguous statistical language as of higher quality (by .34-.80 SD) and as similarly or more supportive (by .16-.27 SD) of policy recommendations than studies described in straightforward causal language. Thus, using statistical rather than causal language to describe nonexperimental findings did not decrease, and may have increased, perceived support for implicitly causal conclusions.
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Registered trials
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.