IDEAS home Printed from https://ideas.repec.org/a/eee/jmvana/v99y2008i10p2472-2478.html
   My bibliography  Save this article

Regression models for multivariate ordered responses via the Plackett distribution

Author

Listed:
  • Forcina, A.
  • Dardanoni, V.

Abstract

We investigate the properties of a class of discrete multivariate distributions whose univariate marginals have ordered categories, all the bivariate marginals, like in the Plackett distribution, have log-odds ratios which do not depend on cut points and all higher-order interactions are constrained to 0. We show that this class of distributions may be interpreted as a discretized version of a multivariate continuous distribution having univariate logistic marginals. Convenient features of this class relative to the class of ordered probit models (the discretized version of the multivariate normal) are highlighted. Relevant properties of this distribution like quadratic log-linear expansion, invariance to collapsing of adjacent categories, properties related to positive dependence, marginalization and conditioning are discussed briefly. When continuous explanatory variables are available, regression models may be fitted to relate the univariate logits (as in a proportional odds model) and the log-odds ratios to covariates.

Suggested Citation

  • Forcina, A. & Dardanoni, V., 2008. "Regression models for multivariate ordered responses via the Plackett distribution," Journal of Multivariate Analysis, Elsevier, vol. 99(10), pages 2472-2478, November.
    • Handle: RePEc:eee:jmvana:v:99:y:2008:i:10:p:2472-2478
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0047-259X(08)00074-2
    Download Restriction: Full text for ScienceDirect subscribers only
    ---><---

    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. D. R. Cox, 2002. "On some models for multivariate binary variables parallel in complexity with the multivariate Gaussian distribution," Biometrika, Biometrika Trust, vol. 89(2), pages 462-469, June.
    2. Bartolucci, Francesco & Forcina, Antonio, 2006. "A Class of Latent Marginal Models for CaptureRecapture Data With Continuous Covariates," Journal of the American Statistical Association, American Statistical Association, vol. 101, pages 786-794, June.
    3. Bartolucci F. & Forcina A. & Dardanoni V., 2001. "Positive Quadrant Dependence and Marginal Modeling in Two-Way Tables With Ordered Margins," Journal of the American Statistical Association, American Statistical Association, vol. 96, pages 1497-1505, December.
    4. Hadar, Josef & Russell, William R, 1969. "Rules for Ordering Uncertain Prospects," American Economic Review, American Economic Association, vol. 59(1), pages 25-34, March.
    5. Bahjat F. Qaqish & Anastasia Ivanova, 2006. "Multivariate logistic models," Biometrika, Biometrika Trust, vol. 93(4), pages 1011-1017, December.
    6. Debashis Ghosh, 2006. "Semiparametric Global Cross‐ratio Models for Bivariate Censored Data," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 33(4), pages 609-619, 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. Domenico Piccolo & Rosaria Simone, 2019. "The class of cub models: statistical foundations, inferential issues and empirical evidence," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 28(3), pages 389-435, September.
    2. Sam Hakim & Simon Neaime, 2011. "An Analysis of the Mobile Telephone Sector in MENA: Potential for Deregulation and Privatization," Working Papers 649, Economic Research Forum, revised 12 Jan 2011.

    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. Oliver Linton & Esfandiar Maasoumi & Yoon-Jae Wang, 2002. "Consistent testing for stochastic dominance: a subsampling approach," CeMMAP working papers 03/02, Institute for Fiscal Studies.
    2. Hooi Hooi Lean & Michael McAleer & Wing-Keung Wong, 2013. "Risk-averse and Risk-seeking Investor Preferences for Oil Spot and Futures," Documentos de Trabajo del ICAE 2013-31, Universidad Complutense de Madrid, Facultad de Ciencias Económicas y Empresariales, Instituto Complutense de Análisis Económico, revised Aug 2013.
    3. Brent A. Gloy & Timothy G. Baker, 2002. "The Importance of Financial Leverage and Risk Aversion in Risk-Management Strategy Selection," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 84(4), pages 1130-1143.
    4. Moshe Levy & Haim Levy, 2013. "Prospect Theory: Much Ado About Nothing?," World Scientific Book Chapters, in: Leonard C MacLean & William T Ziemba (ed.), HANDBOOK OF THE FUNDAMENTALS OF FINANCIAL DECISION MAKING Part I, chapter 7, pages 129-144, World Scientific Publishing Co. Pte. Ltd..
    5. Heller, Yuval & Schreiber, Amnon, 2020. "Short-term investments and indices of risk," Theoretical Economics, Econometric Society, vol. 15(3), July.
    6. Michel M. Denuit & Louis Eeckhoudt, 2010. "A General Index of Absolute Risk Attitude," Management Science, INFORMS, vol. 56(4), pages 712-715, April.
    7. David J. Pannell, 1991. "Pests and pesticides, risk and risk aversion," Agricultural Economics, International Association of Agricultural Economists, vol. 5(4), pages 361-383, August.
    8. Joseph Aharony & Sasson Bar†Yosef, 1987. "Tests of the impact of LIFO adoption on stockholders: A stochastic dominance approach," Contemporary Accounting Research, John Wiley & Sons, vol. 3(2), pages 430-444, March.
    9. Brown, David P., 2017. "New characterizations of increasing risk," Journal of Mathematical Economics, Elsevier, vol. 69(C), pages 7-11.
    10. Chateauneuf, Alain & Cohen, Michele & Meilijson, Isaac, 2004. "Four notions of mean-preserving increase in risk, risk attitudes and applications to the rank-dependent expected utility model," Journal of Mathematical Economics, Elsevier, vol. 40(5), pages 547-571, August.
    11. Lean, Hooi Hooi & McAleer, Michael & Wong, Wing-Keung, 2015. "Preferences of risk-averse and risk-seeking investors for oil spot and futures before, during and after the Global Financial Crisis," International Review of Economics & Finance, Elsevier, vol. 40(C), pages 204-216.
    12. Branda, Martin, 2013. "Diversification-consistent data envelopment analysis with general deviation measures," European Journal of Operational Research, Elsevier, vol. 226(3), pages 626-635.
    13. Tsang, Chun-Kei & Wong, Wing-Keung & Horowitz, Ira, 2016. "A stochastic-dominance approach to determining the optimal home-size purchase: The case of Hong Kong," MPRA Paper 69175, University Library of Munich, Germany.
    14. Lizyayev, Andrey & Ruszczyński, Andrzej, 2012. "Tractable Almost Stochastic Dominance," European Journal of Operational Research, Elsevier, vol. 218(2), pages 448-455.
    15. Yang Yang & Xuezheng Chen & Jing Gu & Hamido Fujita, 2019. "Alleviating Financing Constraints of SMEs through Supply Chain," Sustainability, MDPI, vol. 11(3), pages 1-19, January.
    16. Arvanitis, Stelios & Scaillet, Olivier & Topaloglou, Nikolas, 2020. "Spanning tests for Markowitz stochastic dominance," Journal of Econometrics, Elsevier, vol. 217(2), pages 291-311.
    17. Gollier, Christian, 2021. "A general theory of risk apportionment," Journal of Economic Theory, Elsevier, vol. 192(C).
    18. Zaras, Kazimierz, 2001. "Rough approximation of a preference relation by a multi-attribute stochastic dominance for determinist and stochastic evaluation problems," European Journal of Operational Research, Elsevier, vol. 130(2), pages 305-314, April.
    19. Yaffa Machnes, 2003. "Stochastic Dominance of Pension Plans," Metroeconomica, Wiley Blackwell, vol. 54(1), pages 49-59, February.
    20. Miller-Hooks, Elise & Mahmassani, Hani, 2003. "Path comparisons for a priori and time-adaptive decisions in stochastic, time-varying networks," European Journal of Operational Research, Elsevier, vol. 146(1), pages 67-82, April.

    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:eee:jmvana:v:99:y:2008:i:10:p:2472-2478. 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: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/wps/find/journaldescription.cws_home/622892/description#description .

    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.