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Cited by 1,825Statistical Methods and ApplicationsMultidisciplinary Science and Engineering ResearchPsychometric Methodologies and Testing

Set correlation and contingency tables

Open access
Cohen, Jacob·1988·Applied Psychological Measurement
DOI 10.1177/014662168801200410
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Abstract

Set correlation is a realization of the general multi variate linear model, can be viewed as a multivariate generalization of multiple correlation analysis, and may be employed in the analysis of multivariate data in any form. Set correlation supplements the four methods for analyzing two-way contingency tables de scribed by Zwick and Cramer (1986), and its applica tion to their example is illustrated. It gives the same results for the overall association, and in addition, by the use of nominal scale coding and partialling, it as sesses specific hypotheses about the details of the as sociation. Set correlation includes measures of strength of association (including correlations and proportions of variance), significance tests and estimation, power analysis, and computer programs to implement the calculations. Index terms: canonical analysis, con tingency table analysis, correspondence analysis, gen eral multivariate linear model, multivariate analysis of variance, Pearson chi-square, set correlation.

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  • Cohen J.'s 1988 work on statistical power analysis in behavioural sciences follows with 108 citations.

    “Cohen J.’s 1988 work [39] on statistical power analysis in behavioural sciences follows with 108 citations, showcasing its critical methodological influence.”

    From Evolution of Primary Research Studies in Digital Interventions for Mental Well-Being Promotion from 2004 to 2023: A Bibliometric Analysis of Studies on the Web of Science (2024) · cites this paper as [39]

    The Abstract identifies this paper as a study of set correlation and contingency tables, not Cohen’s work on statistical power analysis. The References list Cohen’s 1988 Statistical power analysis as a separate work. Our copy does not establish the claimed 108-citation count. (LLM, conf=0.86)

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  • A previous VR intervention for anxiety disorders among a general population sample had an estimated effect size of g=0.78 (medium) compared with minimal-attention controls and g=0.90 (large) with no-treatment controls.

    “However, a previous VR intervention for anxiety disorders among a general population sample had an estimated effect size of g=0.78 (medium) compared with minimal-attention controls and g=0.90 (large) with no-treatment controls [26,27].”

    From A Virtual Reality-Assisted Cognitive Behavioral Therapy for and With Inuit in Québec: Protocol for a Proof-of-Concept Randomized Controlled Trial (2023) · cites this paper as [27]

    The Results section analyzes associations between religion and responses to an abortion survey. A search of our full-text copy for VR anxiety interventions, the two control conditions, g=0.78 and g=0.90, and medium/large effect-size labels found no passage addressing the claim. (LLM, conf=0.78)

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  • The strength of correlation between the seven cognitive domains within the sample was generally moderate, with values ranging from r=0.19 to r=0.49.

    “The strength of correlation between the seven cognitive domains within our sample was generally in the ‘moderate’ range (Cohen, 1988), with values ranging from r=0.19 to r=0.49 (full results are available online in Supplemental Table S1).”

    From Can mild traumatic brain injury alter cognition chronically? A LIMBIC-CENC multicenter study. (2023) · cites this paper as Cohen, 1988

    The Results section discusses correlations in an analysis of religion and abortion responses, but it gives no rule classifying correlations as ‘moderate.’ Searches for moderate-correlation thresholds and for the seven cognitive domains found no relevant passage in this paper. The cited paper’s References section lists a separate 1988 Cohen book, but the paper itself does not state the classification attributed to it. (LLM, conf=0.76)

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Research works printed but not linked: 1

  1. Cohen, J., & Cohen, P. (1983). Applied multiple regres- sion/correlation for the behavioral sciences (2nd ed.). Hillsdale NJ: Erlbaum.

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Authors
Cohen, J.
Affiliations
New York University (US)
Corresponding author
Cohen, Jacob
Venue
Applied Psychological Measurement
Publisher
SAGE Publications
Published
1988-12
Volume
12
Issue
4
Pages
425-434
ISSN
  • 0146-6216 (ISSN-L)
  • 1552-3497
DOI
10.1177/014662168801200410
OpenAlex
W1979191094
Cited by
1,825
References
15
Citations by year
2026: 436 · 2025: 266 · 2024: 258 · 2023: 295 · 2022: 186 · 2021: 122 · 2020: 47 · 2019: 37 · 2018: 24 · 2017: 20 · 2016: 23 · 2015: 9 · 2014: 15 · 2013: 7 · 2012: 9
FWCI
0.98
Type
journal article
Language
en
Open access
Licence
journals.sagepub.com/page/policies/text-and-data-mining-license (tdm)
Locations
  • Applied Psychological Measurement (publishedVersion)
  • University of Minnesota Digital Conservancy (University of Minnesota) (submittedVersion)
Topics
  • Physical Sciences › Mathematics › Statistics and Probability › Statistical Methods and Applications
  • Social Sciences › Decision Sciences › Statistics, Probability and Uncertainty › Multidisciplinary Science and Engineering Research
  • Social Sciences › Decision Sciences › Management Science and Operations Research › Psychometric Methodologies and Testing
Keywords
contingency tables, canonical analysis, correspondence analysis, multivariate linear models, multiple correlation, associative strength, power analysis, significance testing

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