Model Averaging in Factor Analysis: An Analysis of Olympic Decathlon Data
This article presents a multivariate analysis of Olympic decathlon data based on maximum likelihood factor analysis. All results explicitly account for model selection uncertainty, which is inherent in any data-based selection process but mostly ignored in reports related to multivariate sports data. For this purpose, some well-established frequentist procedures that have so far been applied almost exclusively to regression analysis are adopted and transferred to the factor analytical context. The findings support the claim that decathlon contests consist of three dimensions. These dimensions seem to be similar to, but not exactly the same, as those found by Cox and Dunn (2002) via hierarchical cluster analysis.
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Volume (Year): 7 (2011)
Issue (Month): 1 (January)
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Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:
- Schomaker, Michael & Wan, Alan T.K. & Heumann, Christian, 2010. "Frequentist Model Averaging with missing observations," Computational Statistics & Data Analysis, Elsevier, vol. 54(12), pages 3336-3347, December.
- Ludwig Fahrmeir & Alexander Raach, 2007. "A Bayesian Semiparametric Latent Variable Model for Mixed Responses," Psychometrika, Springer;The Psychometric Society, vol. 72(3), pages 327-346, September.
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