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A Note on the Folly of Cross-Sectional Operationalizations of Generations

Published online by Cambridge University Press:  02 October 2015

Cort W. Rudolph*
Affiliation:
Department of Psychology, Saint Louis University
*
Correspondence concerning this article should be addressed to Cort W. Rudolph, Department of Psychology, Saint Louis University, 3700 Lindell Boulevard, Morrissey Hall, Room 2827, Saint Louis, MO 63108. E-mail: [email protected]

Extract

Costanza and Finkelstein (2015) have justly argued that cross-sectional operationalizations of generational groups represent a confound that constrains the ability to unequivocally separate the effects of age and period. A related statistical argument against this practice bears consideration as well. Namely, cross-sectional operationalizations of generations have the potential to unduly inflate type two-error rates when compared with the analysis of simple age effects. This is a problem because true age effects can be erroneously ignored in studies where age is artificially split into assumed generational groups. Indeed, the argument against artificially bifurcating continuous data is not new (e.g., Cohen, 1983), however past attempts to make inferences about generational effects in cross-sectional designs present an opportunity to investigate the particularly insidious nature of this practice and its implications. To demonstrate the problem at hand, let us consider a brief empirical example by virtue of a simulation study.

Type
Commentaries
Copyright
Copyright © Society for Industrial and Organizational Psychology 2015 

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References

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