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Multiple Comparisons in a Regression Approach

Bibliographic Data

ID13670893
AuthorsJohn D Williams (0000-0002-4681-3360, University of North Dakota, corresponding author)
Year1972
Volume30
Issue2
Pages639-647
Publication date1972-04-01
Peer ReviewedYes
Open AccessYes
TypeARTICLE
VenuePsychological Reports (JOURNAL)
Journal identifiersISSN: 0033-2941 • E-ISSN: 1558-691X
PublisherSAGE Publishing (PUBLISHER • US)
DOI10.2466/pr0.1972.30.2.639
OpenAlexW2127655664
LanguageEN
Citations received1
References cited12

In using multiple regression as a data-analysis technique, one problem that might arise is the overuse of a full model with several restricted models, without adjusting the probability level. Such an approach would violate the apparent (or tabled) probability level. This has long been a concern in statistics. The intent of the present paper has been to reconceptualize two of the better known multiple-comparison procedures in a multiple regression approach. The change in the regression approach requires assessing the results of multiple uses of a full model to a correct distribution rather than a straightforward use of the F distribution

Cross-sectional regression · Econometrics · Linear regression · Polynomial regression · Probability distribution · Regression · Regression analysis · Regression diagnostic · Statistics · Advanced Statistical Methods and Models · Computer Science · Mathematics · Optimal Experimental Design Methods · Psychology · Statistical Methods in Clinical Trials

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    William T Bielby, James R Kluegel•Sociological Methodology•1977

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    B J Winer•1962

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    Olive Jean Dunn•Journal of the American…•1961

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    David B Duncan•Biometrics•1955

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    Earl Jennings•Multivariate Behavioral Research•1967

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    Jacob Cohen•Psychological Bulletin•1968

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Unique citing works1
Citations per year0,02
Citation span1977 - 1977 (1)
Citation velocityhistorical
Highly citedNo
Citation typesNeutral: 1

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