Pseudoreplication Revisited

Heffner, Robert A.; Butler, Mark J.; Reilly, Colleen Keelan

doi:10.2307/2265754

Cited by 139Ecology and Vegetation Dynamics StudiesStatistical Methods and Bayesian InferenceStatistical Methods and Applications

Pseudoreplication Revisited

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Heffner, Robert A., Butler, Mark J., Reilly, Colleen Keelan·1996·Ecology

DOI 10.2307/2265754

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Abstract

during 1960-1980 for evidence of pseudoreplication (Hurlbert 1984).Pseudoreplication is defined by Hurlbert (1984: 18) as

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Pseudoreplication has been addressed repeatedly in ecology, agriculture, psychology, and neuroscience and acknowledged as one of the most common statistical mistakes in scientific literature.
“Pseudoreplication has been addressed repeatedly in ecology, agriculture, psychology, and neuroscience and acknowledged as one of the most common statistical mistakes in scientific literature4–9.”
From A practical solution to pseudoreplication bias in single-cell studies (2021) · cites this paper as [5]
The Results (page not provided) report pseudoreplication in about one in eight ecological field experiments reviewed, and the passage labeled Abstract describes extensive discussion of the problem among ecologists. The paper does not establish its frequency in agriculture, psychology, or neuroscience, or rank it among the most common statistical mistakes across scientific literature. (LLM, conf=0.86)
Experimental — accuracy not yet measured
Applying statistical inference to replicates that are not statistically independent without properly accounting for their correlation structure will inflate type 1 error rates and lead to spurious results.
“Here we hope to address pseudoreplication in single-cell analyses by demonstrating what a large and long-standing body of statistical literature already confirms: applying statistical inference to replicates that are not statistically independent without properly accounting for their correlation structure will inflate type 1 error rates and lead to spurious results4–6,9,25–28.”
From A practical solution to pseudoreplication bias in single-cell studies (2021) · cites this paper as [5]
The paper defines pseudoreplication to include applying inferential statistics when experimental units are not statistically independent. It says improper replication usually underestimates or confounds variation, increasing the risk of a Type I error, and that conclusions may be limited or invalid. The claim’s categorical “will inflate” and “lead to” are stronger than the paper’s qualified wording. The supplied passages are labeled Abstract; page numbers are unavailable. (LLM, conf=0.85)
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Pseudoreplication and the Design of Ecological Field Experiments
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Crowley, P. H. 1992. Resampling methods for computation- intensive data analyses in ecology and evolution. Annual Review Ecology and Systematics 23:405-447.
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Authors: Heffner, R. A., Butler, M. J., & Reilly, C. K.
Venue: Ecology
Publisher: Wiley
Published: 1996-12
Volume: 77
Issue: 8
Pages: 2558-2562
ISSN: 0012-9658 (ISSN-L)
1939-9170
DOI: 10.2307/2265754
OpenAlex: W4240529425
Semantic Scholar: 79be96546a85de95d191acaf9aaaf35799fb84c4
Cited by: 139
References: 9
Citations by year: 2026: 3 · 2025: 5 · 2024: 6 · 2023: 6 · 2022: 11 · 2021: 4 · 2020: 5 · 2019: 3 · 2018: 4 · 2017: 7 · 2016: 7 · 2015: 5 · 2014: 4 · 2013: 3 · 2012: 6
FWCI: 2.44
Type: journal article
Language: en
Open access: green
digitalcommons.odu.edu
Licence: onlinelibrary.wiley.com/termsAndConditions#vor (vor)
Locations: Ecology (publishedVersion)
ODU Digital Commons (Old Dominion University) (submittedVersion)
Topics: Physical Sciences › Environmental Science › Nature and Landscape Conservation › Ecology and Vegetation Dynamics Studies
Physical Sciences › Mathematics › Statistics and Probability › Statistical Methods and Bayesian Inference
Physical Sciences › Mathematics › Statistics and Probability › Statistical Methods and Applications
Keywords: pseudoreplication, statistical inference, repeated measures, sample size, statistical power, ecological data analysis

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