IDEAS home Printed from https://ideas.repec.org/a/bpj/jqsprt/v7y2011i1n4.html
   My bibliography  Save this article

Model Averaging in Factor Analysis: An Analysis of Olympic Decathlon Data

Author

Listed:
  • Schomaker Michael

    (Ludwig-Maximilians-Universität)

  • Heumann Christian

    (Ludwig-Maximilians-Universität)

Abstract

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.

Suggested Citation

  • Schomaker Michael & Heumann Christian, 2011. "Model Averaging in Factor Analysis: An Analysis of Olympic Decathlon Data," Journal of Quantitative Analysis in Sports, De Gruyter, vol. 7(1), pages 1-15, January.
  • Handle: RePEc:bpj:jqsprt:v:7:y:2011:i:1:n:4
    DOI: 10.2202/1559-0410.1249
    as

    Download full text from publisher

    File URL: https://doi.org/10.2202/1559-0410.1249
    Download Restriction: For access to full text, subscription to the journal or payment for the individual article is required.

    File URL: https://libkey.io/10.2202/1559-0410.1249?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Hirotugu Akaike, 1987. "Factor analysis and AIC," Psychometrika, Springer;The Psychometric Society, vol. 52(3), pages 317-332, September.
    2. Woolf Anne & Ansley Les & Bidgood Penelope, 2007. "Grouping of Decathlon Disciplines," Journal of Quantitative Analysis in Sports, De Gruyter, vol. 3(4), pages 1-15, October.
    3. Claeskens,Gerda & Hjort,Nils Lid, 2008. "Model Selection and Model Averaging," Cambridge Books, Cambridge University Press, number 9780521852258, October.
    4. 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.
    5. 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.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Schomaker, Michael & Heumann, Christian, 2014. "Model selection and model averaging after multiple imputation," Computational Statistics & Data Analysis, Elsevier, vol. 71(C), pages 758-770.
    2. Wimmer Valentin & Fenske Nora & Pyrka Patricia & Fahrmeir Ludwig, 2011. "Exploring Competition Performance in Decathlon Using Semi-Parametric Latent Variable Models," Journal of Quantitative Analysis in Sports, De Gruyter, vol. 7(4), pages 1-21, October.
    3. Shaobo Jin & Sebastian Ankargren, 2019. "Frequentist Model Averaging in Structural Equation Modelling," Psychometrika, Springer;The Psychometric Society, vol. 84(1), pages 84-104, March.
    4. Fröhlich, Michael & Gassmann, Freya & Emrich, Eike (ed.), 2015. "Zur Strukturanalyse des Mehrkampfes in der Leichtathletik: Eine empirische Studie zum Zusammenhang von Leistung und Erfolg im Siebenkampf der Frauen und Zehnkampf der Männer," Schriften des Europäischen Instituts für Sozioökonomie e.V., European Institute for Socioeconomics (EIS), Saarbrücken, volume 11, number 11, March.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Hai Wang & Xinjie Chen & Nancy Flournoy, 2016. "The focused information criterion for varying-coefficient partially linear measurement error models," Statistical Papers, Springer, vol. 57(1), pages 99-113, March.
    2. Ogasawara, Haruhiko, 2016. "Bias correction of the Akaike information criterion in factor analysis," Journal of Multivariate Analysis, Elsevier, vol. 149(C), pages 144-159.
    3. Yuting Wei & Qihua Wang & Wei Liu, 2021. "Model averaging for linear models with responses missing at random," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 73(3), pages 535-553, June.
    4. Xinyu Zhang & Alan T. K. Wan & Sherry Z. Zhou, 2011. "Focused Information Criteria, Model Selection, and Model Averaging in a Tobit Model With a Nonzero Threshold," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 30(1), pages 132-142, June.
    5. Wimmer Valentin & Fenske Nora & Pyrka Patricia & Fahrmeir Ludwig, 2011. "Exploring Competition Performance in Decathlon Using Semi-Parametric Latent Variable Models," Journal of Quantitative Analysis in Sports, De Gruyter, vol. 7(4), pages 1-21, October.
    6. Magnus, Jan R. & Wan, Alan T.K. & Zhang, Xinyu, 2011. "Weighted average least squares estimation with nonspherical disturbances and an application to the Hong Kong housing market," Computational Statistics & Data Analysis, Elsevier, vol. 55(3), pages 1331-1341, March.
    7. Zhang, Xinyu & Wan, Alan T.K. & Zou, Guohua, 2013. "Model averaging by jackknife criterion in models with dependent data," Journal of Econometrics, Elsevier, vol. 174(2), pages 82-94.
    8. Jiwon Lee & Midam An & Yongku Kim & Jung-In Seo, 2021. "Optimal Allocation for Electric Vehicle Charging Stations," Energies, MDPI, vol. 14(18), pages 1-10, September.
    9. Benjamin G Schultz & Catherine J Stevens & Peter E Keller & Barbara Tillmann, 2013. "A Sequence Identification Measurement Model to Investigate the Implicit Learning of Metrical Temporal Patterns," PLOS ONE, Public Library of Science, vol. 8(9), pages 1-1, September.
    10. Kitagawa, Toru & Muris, Chris, 2016. "Model averaging in semiparametric estimation of treatment effects," Journal of Econometrics, Elsevier, vol. 193(1), pages 271-289.
    11. Daniela Andreini & Diego Rinallo & Giuseppe Pedeliento & Mara Bergamaschi, 2017. "Brands and Religion in the Secularized Marketplace and Workplace: Insights from the Case of an Italian Hospital Renamed After a Roman Catholic Pope," Journal of Business Ethics, Springer, vol. 141(3), pages 529-550, March.
    12. Jeffrey S. Racine & Qi Li & Dalei Yu & Li Zheng, 2023. "Optimal Model Averaging of Mixed-Data Kernel-Weighted Spline Regressions," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 41(4), pages 1251-1261, October.
    13. Andreas Wienke & Anne M. Herskind & Kaare Christensen & Axel Skytthe & Anatoli I. Yashin, 2002. "The influence of smoking and BMI on heritability in susceptibility to coronary heart disease," MPIDR Working Papers WP-2002-003, Max Planck Institute for Demographic Research, Rostock, Germany.
    14. Philippe Goulet Coulombe & Maxime Leroux & Dalibor Stevanovic & Stéphane Surprenant, 2022. "How is machine learning useful for macroeconomic forecasting?," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 37(5), pages 920-964, August.
    15. Davide Fiaschi & Andrea Mario Lavezzi & Angela Parenti, 2020. "Deep and Proximate Determinants of the World Income Distribution," Review of Income and Wealth, International Association for Research in Income and Wealth, vol. 66(3), pages 677-710, September.
    16. Byrd, T. A. & Marshall, T. E., 1997. "Relating information technology investment to organizational performance: a causal model analysis," Omega, Elsevier, vol. 25(1), pages 43-56, February.
    17. Berry, Brian J.L. & Okulicz-Kozaryn, Adam, 2008. "Are there ENSO signals in the macroeconomy," Ecological Economics, Elsevier, vol. 64(3), pages 625-633, January.
    18. Nicos Nicolaou & Scott Shane, 2019. "Common genetic effects on risk-taking preferences and choices," Journal of Risk and Uncertainty, Springer, vol. 59(3), pages 261-279, December.
    19. Stephen Richards, 2010. "Author's response," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 173(4), pages 920-924, October.
    20. Ken B Hanscombe & Maciej Trzaskowski & Claire M A Haworth & Oliver S P Davis & Philip S Dale & Robert Plomin, 2012. "Socioeconomic Status (SES) and Children's Intelligence (IQ): In a UK-Representative Sample SES Moderates the Environmental, Not Genetic, Effect on IQ," PLOS ONE, Public Library of Science, vol. 7(2), pages 1-16, February.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:bpj:jqsprt:v:7:y:2011:i:1:n:4. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Peter Golla (email available below). General contact details of provider: https://www.degruyter.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.