Looking for Validity or Testing It? The Perils of Stepwise Regression, Extreme-Scores Analysis, Heteroscedasticity, and Measurement Error

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Serval ID
serval:BIB_C442A0C8EDFC
Type
Article: article from journal or magazin.
Collection
Publications
Title
Looking for Validity or Testing It? The Perils of Stepwise Regression, Extreme-Scores Analysis, Heteroscedasticity, and Measurement Error
Journal
Personality and Individual Differences
Author(s)
Antonakis J., Dietz J.
ISSN
0191-8869
Publication state
Published
Issued date
02/2011
Peer-reviewed
Oui
Volume
50
Number
3
Pages
409-415
Language
english
Abstract
When researchers introduce a new test they have to demonstrate that it is valid, using unbiased designs and suitable statistical procedures. In this article we use Monte Carlo analyses to highlight how incorrect statistical procedures (i.e., stepwise regression, extreme scores analyses) or ignoring regression assumptions (e.g., heteroscedasticity) contribute to wrong validity estimates. Beyond these demonstrations, and as an example, we re-examined the results reported by Warwick, Nettelbeck, and Ward (2010) concerning the validity of the Ability Emotional Intelligence Measure (AEIM). Warwick et al. used the wrong statistical procedures to conclude that the AEIM was incrementally valid beyond intelligence and personality traits in predicting various outcomes. In our re-analysis, we found that the reliability-corrected multiple correlation of their measures with personality and intelligence was up to .69. Using robust statistical procedures and appropriate controls, we also found that the AEIM did not predict incremental variance in GPA, stress, loneliness, or well-being, demonstrating the importance for testing validity instead of looking for it.
Keywords
emotional intelligence, general intelligence, personality, validity, errors-in-variables, heteroscedasticity, truncation, Monte Carlo
Web of science
Open Access
Yes
Create date
10/09/2010 21:47
Last modification date
09/05/2019 0:55
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