IDEAS home Printed from https://ideas.repec.org/a/spr/psycho/v80y2015i2p516-534.html
   My bibliography  Save this article

Constrained Stochastic Extended Redundancy Analysis

Author

Listed:
  • Wayne DeSarbo
  • Heungsun Hwang
  • Ashley Stadler Blank
  • Eelco Kappe

Abstract

We devise a new statistical methodology called constrained stochastic extended redundancy analysis (CSERA) to examine the comparative impact of various conceptual factors, or drivers, as well as the specific predictor variables that contribute to each driver on designated dependent variable(s). The technical details of the proposed methodology, the maximum likelihood estimation algorithm, and model selection heuristics are discussed. A sports marketing consumer psychology application is provided in a Major League Baseball (MLB) context where the effects of six conceptual drivers of game attendance and their defining predictor variables are estimated. Results compare favorably to those obtained using traditional extended redundancy analysis (ERA). Copyright The Psychometric Society 2015

Suggested Citation

  • Wayne DeSarbo & Heungsun Hwang & Ashley Stadler Blank & Eelco Kappe, 2015. "Constrained Stochastic Extended Redundancy Analysis," Psychometrika, Springer;The Psychometric Society, vol. 80(2), pages 516-534, June.
    • Handle: RePEc:spr:psycho:v:80:y:2015:i:2:p:516-534
    DOI: 10.1007/s11336-013-9385-6
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/10.1007/s11336-013-9385-6
    Download Restriction: Access to full text is restricted to subscribers.
    File URL: https://libkey.io/10.1007/s11336-013-9385-6?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. Stephen Allan, 2004. "Satellite television and football attendance: the not so super effect," Applied Economics Letters, Taylor & Francis Journals, vol. 11(2), pages 123-125.
    2. Andrew Welki & Thomas Zlatoper, 1999. "U.S. professional football game-day attendance," Atlantic Economic Journal, Springer;International Atlantic Economic Society, vol. 27(3), pages 285-298, September.
    3. Heungsun Hwang & Hye Suk & Jang-Han Lee & D. Moskowitz & Jooseop Lim, 2012. "Functional Extended Redundancy Analysis," Psychometrika, Springer;The Psychometric Society, vol. 77(3), pages 524-542, July.
    4. Raja P. Velu, 1991. "Reduced Rank Models with Two Sets of Regressors," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 40(1), pages 159-170, March.
    5. McDonald, Mark & Rascher, Daniel, 2000. "Does Bat Day Make Cents? The Effect of Promotions on the Demand for Major League Baseball," MPRA Paper 25739, University Library of Munich, Germany.
    6. Izenman, Alan Julian, 1975. "Reduced-rank regression for the multivariate linear model," Journal of Multivariate Analysis, Elsevier, vol. 5(2), pages 248-264, June.
    7. Seth R. Gitter & Thomas A. Rhoads, 2010. "Determinants of Minor League Baseball Attendance," Journal of Sports Economics, , vol. 11(6), pages 614-628, December.
    8. Baimbridge, Mark & Cameron, Samuel & Dawson, Peter, 1996. "Satellite Television and the Demand for Football: A Whole New Ball Game?," Scottish Journal of Political Economy, Scottish Economic Society, vol. 43(3), pages 317-333, August.
    9. Michel Wedel & Wayne DeSarbo, 1995. "A mixture likelihood approach for generalized linear models," Journal of Classification, Springer;The Classification Society, vol. 12(1), pages 21-55, March.
    10. Arnold Wollenberg, 1977. "Redundancy analysis an alternative for canonical correlation analysis," Psychometrika, Springer;The Psychometric Society, vol. 42(2), pages 207-219, June.
    11. Robert J. Lemke & Matthew Leonard & Kelebogile Tlhokwane, 2010. "Estimating Attendance at Major League Baseball Games for the 2007 Season," Journal of Sports Economics, , vol. 11(3), pages 316-348, June.
    12. Heungsun Hwang & Yoshio Takane, 2004. "Generalized structured component analysis," Psychometrika, Springer;The Psychometric Society, vol. 69(1), pages 81-99, March.
    13. Eelco Kappe & Ashley Stadler Blank & Wayne S. DeSarbo, 2014. "A General Multiple Distributed Lag Framework for Estimating the Dynamic Effects of Promotions," Management Science, INFORMS, vol. 60(6), pages 1489-1510, June.
    14. Elise M. Beckman & Wenqiang Cai & Rebecca M. Esrock & Robert J. Lemke, 2012. "Explaining Game-to-Game Ticket Sales for Major League Baseball Games Over Time," Journal of Sports Economics, , vol. 13(5), pages 536-553, October.
    15. S. le Cessie & J. C. van Houwelingen, 1992. "Ridge Estimators in Logistic Regression," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 41(1), pages 191-201, March.
    16. Takane, Yoshio & Hwang, Heungsun, 2005. "An extended redundancy analysis and its applications to two practical examples," Computational Statistics & Data Analysis, Elsevier, vol. 49(3), pages 785-808, June.
    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. Kappe, Eelco & Stadler Blank, Ashley & DeSarbo, Wayne S., 2018. "A random coefficients mixture hidden Markov model for marketing research," International Journal of Research in Marketing, Elsevier, vol. 35(3), pages 415-431.

    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. Eelco Kappe & Ashley Stadler Blank & Wayne S. DeSarbo, 2014. "A General Multiple Distributed Lag Framework for Estimating the Dynamic Effects of Promotions," Management Science, INFORMS, vol. 60(6), pages 1489-1510, June.
    2. Heungsun Hwang & Hye Suk & Yoshio Takane & Jang-Han Lee & Jooseop Lim, 2015. "Generalized Functional Extended Redundancy Analysis," Psychometrika, Springer;The Psychometric Society, vol. 80(1), pages 101-125, March.
    3. Kappe, Eelco & Stadler Blank, Ashley & DeSarbo, Wayne S., 2018. "A random coefficients mixture hidden Markov model for marketing research," International Journal of Research in Marketing, Elsevier, vol. 35(3), pages 415-431.
    4. Minjung Kyung & Ju-Hyun Park & Ji Yeh Choi, 2022. "Bayesian Mixture Model of Extended Redundancy Analysis," Psychometrika, Springer;The Psychometric Society, vol. 87(3), pages 946-966, September.
    5. Steffen Q. Mueller, 2020. "Pre- and within-season attendance forecasting in Major League Baseball: a random forest approach," Applied Economics, Taylor & Francis Journals, vol. 52(41), pages 4512-4528, September.
    6. Grant Allan & Graeme Roy, 2008. "Does Television Crowd Out Spectators?," Journal of Sports Economics, , vol. 9(6), pages 592-605, December.
    7. Pietro Giorgio Lovaglio & Gianmarco Vacca & Stefano Verzillo, 2016. "Human capital estimation in higher education," Advances in Data Analysis and Classification, Springer;German Classification Society - Gesellschaft für Klassifikation (GfKl);Japanese Classification Society (JCS);Classification and Data Analysis Group of the Italian Statistical Society (CLADAG);International Federation of Classification Societies (IFCS), vol. 10(4), pages 465-489, December.
    8. Jeffery Borland, 2003. "Demand for Sport," Oxford Review of Economic Policy, Oxford University Press and Oxford Review of Economic Policy Limited, vol. 19(4), pages 478-502, Winter.
    9. Pietro Lovaglio & Roberto Boselli, 2015. "Simulation studies of structural equation models with covariates in a redundancy analysis framework," Quality & Quantity: International Journal of Methodology, Springer, vol. 49(3), pages 881-890, May.
    10. Tim Wallrafen & Tim Pawlowski & Christian Deutscher, 2019. "Substitution in Sports: The Case of Lower Division Football Attendance," Journal of Sports Economics, , vol. 20(3), pages 319-343, April.
    11. Alexander John Bond & Francesco Addesa, 2020. "Competitive Intensity, Fans’ Expectations, and Match-Day Tickets Sold in the Italian Football Serie A, 2012-2015," Journal of Sports Economics, , vol. 21(1), pages 20-43, January.
    12. Adam Cox, 2018. "Spectator Demand, Uncertainty of Results, and Public Interest," Journal of Sports Economics, , vol. 19(1), pages 3-30, January.
    13. Catherine C. Gropper & Benjamin C. Anderson, 2018. "Sellout, Blackout, or Get Out," Journal of Sports Economics, , vol. 19(3), pages 332-370, April.
    14. Hojun Sung & Brian M. Mills, 2018. "Estimation of game-level attendance in major league soccer: Outcome uncertainty and absolute quality considerations," Sport Management Review, Taylor & Francis Journals, vol. 21(5), pages 519-532, December.
    15. Pietro Giorgio Lovaglio & Giuseppe Folloni, 2011. "The estimation of Human Capital in structural models with flexible specification," Working Papers 11, AlmaLaurea Inter-University Consortium.
    16. Heungsun Hwang & Hye Suk & Jang-Han Lee & D. Moskowitz & Jooseop Lim, 2012. "Functional Extended Redundancy Analysis," Psychometrika, Springer;The Psychometric Society, vol. 77(3), pages 524-542, July.
    17. Budzinski, Oliver & Feddersen, Arne, 2015. "Grundlagen der Sportnachfrage: Theorie und Empirie der Einflussfaktoren auf die Zuschauernachfrage," Ilmenau Economics Discussion Papers 94, Ilmenau University of Technology, Institute of Economics.
    18. Dominik Schreyer, 2019. "Football spectator no-show behaviour in the German Bundesliga," Applied Economics, Taylor & Francis Journals, vol. 51(45), pages 4882-4901, September.
    19. Russell Ormiston, 2014. "Attendance Effects of Star Pitchers in Major League Baseball," Journal of Sports Economics, , vol. 15(4), pages 338-364, August.
    20. Jason P. Berkowitz & Craig A. Depken II & John M. Gandar, 2018. "The Conversion of Money Lines Into Win Probabilities," Journal of Sports Economics, , vol. 19(7), pages 990-1015, October.

    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:spr:psycho:v:80:y:2015:i:2:p:516-534. 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: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.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.