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Current misuses of multiple regression for investigating bivariate hypotheses: an example from the organizational domain

Overview of attention for article published in Behavior Research Methods, October 2013
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Title
Current misuses of multiple regression for investigating bivariate hypotheses: an example from the organizational domain
Published in
Behavior Research Methods, October 2013
DOI 10.3758/s13428-013-0407-1
Pubmed ID
Authors

Thomas A. O’Neill, Matthew J. W. McLarnon, Travis J. Schneider, Robert C. Gardner

Abstract

By definition, multiple regression (MR) considers more than one predictor variable, and each variable's beta will depend on both its correlation with the criterion and its correlation with the other predictor(s). Despite ad nauseam coverage of this characteristic in organizational psychology and statistical texts, researchers' applications of MR in bivariate hypothesis testing has been the subject of recent and renewed interest. Accordingly, we conducted a targeted survey of the literature by coding articles, covering a five-year span from two top-tier organizational journals, that employed MR for testing bivariate relations. The results suggest that MR coefficients, rather than correlation coefficients, were most common for testing hypotheses of bivariate relations, yet supporting theoretical rationales were rarely offered. Regarding the potential impact on scientific advancement, in almost half of the articles reviewed (44 %), at least one conclusion of each study (i.e., that the hypothesis was or was not supported) would have been different, depending on the author's use of correlation or beta to test the bivariate hypothesis. It follows that inappropriate decisions to interpret the correlation versus the beta will affect the accumulation of consistent and replicable scientific evidence. We conclude with recommendations for improving bivariate hypothesis testing.

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 33 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
South Africa 1 3%
Unknown 32 97%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 6 18%
Researcher 5 15%
Student > Bachelor 3 9%
Professor > Associate Professor 3 9%
Student > Master 3 9%
Other 6 18%
Unknown 7 21%
Readers by discipline Count As %
Psychology 12 36%
Business, Management and Accounting 3 9%
Social Sciences 3 9%
Medicine and Dentistry 3 9%
Agricultural and Biological Sciences 1 3%
Other 4 12%
Unknown 7 21%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 1. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 25 July 2014.
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#20,656,820
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Outputs from Behavior Research Methods
#1,980
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Outputs of similar age
#169,529
of 224,376 outputs
Outputs of similar age from Behavior Research Methods
#21
of 26 outputs
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