Sense and nonsense in hierarchical regression analysis

Comment on Smyth

Bibliographic Data

ID11562425
AuthorsElazar J Pedhazur (corresponding author)
Year1984
Volume46
Issue2
Pages479-482
Publication date1984-02-01
Peer ReviewedYes
Open AccessNo
TypeARTICLE
VenueJournal of Personality and Social Psychology (JOURNAL)
Journal identifiersISSN: 0022-3514 • E-ISSN: 1939-1315
PublisherAmerican Psychological Association (PUBLISHER • US)
DOI10.1037/0022-3514.46.2.479
OpenAlexW1969462188
LanguageEN
Citations received3
References cited5

Hierarchical multiple regression analysis is popular among social scientists. Regrettably,, however, one often encounters the use of hierarchical analysis with what appear to be utter disregard of its requirements and lack of understanding of the nature of the answers it provides (for extensive discussions, see Cohen & Cohen, 1975; Pedhazur, 1982). The purpose of this comment is to discuss incorrect applications of hierarchical analyses in an article by Smyth (1982) published in this journal. It should be noted that the comment is addressed exclusively to this aspect of Smyth's article. Specifically, it deals with the first two paragraphs of his Results section and with his Table 1 (Smyth, 1982, pp. 558-559). Smyth (1982) stated that he resorted to hierarchical regression analysis since analyses of covariance (ANCOVAS) would ignore the possibility of the covariate (neuroticism) interacting with the experimental manipulations (p. 558). Anyone familiar with presentations of conventional (e.g., Edwards, 1972; Kirk, 1968; Winer, 1971) cannot but be puzzled by Smyth's statement, because such presentations underscore the importance of testing whether the covariate interacts with the treatments (i.e., homogeneity of within-groups regression coefficients) as a prerequisite for tests among adjusted means. Although it is true that ANCOVA can be more efficiently accomplished via hierarchical regression analysis (see Cohen & Cohen, 1975; Pedhazur, 1982), the hypotheses tested and

Multilevel model · Nonsense · Psychoanalysis · Regression · Regression analysis · Statistics · Advanced Statistical Methods and Models · Mathematics · Psychology · Social Psychology

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