The Worst Performance Rule as Moderation: New Methods for Worst Performance Analysis
- Publikationstyp:
- Zeitschriftenaufsatz
- Metadaten:
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- Abstract
- <jats:p>Worst performance in cognitive processing tasks shows larger relationships to general intelligence than mean or best performance. This so called Worst Performance Rule (WPR) is of major theoretical interest for the field of intelligence research, especially for research on mental speed. In previous research, the increases in correlations between task performance and general intelligence from best to worst performance were mostly described and not tested statistically. We conceptualized the WPR as moderation, since the magnitude of the relation between general intelligence and performance in a cognitive processing task depends on the performance band or percentile of performance. On the one hand, this approach allows testing the WPR for statistical significance and on the other hand, it may simplify the investigation of possible constructs that may influence the WPR. The application of two possible implementations of this approach is shown and compared to results of a traditional worst performance analysis. The results mostly replicate the WPR. Beyond that, a comparison of results on the level of unstandardized relationships (e.g., covariances or unstandardized regression weights) to results on the level of standardized relationships (i.e., correlations) indicates that increases in the inter-individual standard deviation from best to worst performance may play a crucial role for the WPR. Altogether, conceptualizing the WPR as moderation provides a new and straightforward way to conduct Worst Performance Analysis and may help to incorporate the WPR more prominently into empirical practice of intelligence research.</jats:p>
- Autoren
- Gidon Frischkorn
- Anna-Lena Schubert
- Andreas Neubauer
- Dirk Hagemann
- DOI
- 10.3390/jintelligence4030009
- eISSN
- 2079-3200
- Ausgabe der Veröffentlichung
- 3
- Zeitschrift
- Journal of Intelligence
- Sprache
- en
- Online publication date
- 2016
- Paginierung
- 9 - 9
- Status
- Published online
- Herausgeber
- MDPI AG
- Herausgeber URL
- http://dx.doi.org/10.3390/jintelligence4030009
- Datum der Datenerfassung
- 2024
- Titel
- The Worst Performance Rule as Moderation: New Methods for Worst Performance Analysis
- Ausgabe der Zeitschrift
- 4
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