IDEAS home Printed from https://ideas.repec.org/p/hhs/sduhec/2013_006.html
   My bibliography  Save this paper

A simple but efficient approach to the analysis of multilevel data

Author

Listed:

Abstract

Much research in health economics revolves around the analysis of hierarchically structured data. For instance, combining characteristics of patients with information pertaining to the general practice (GP) clinic providing treatment is called for in order to investigate important features of the underlying nested structure. In this paper we offer a new treatment of the two-level random-intercept model and state equivalence results for specific estimators, including popular two-step estimators. We show that a certain encompassing regression equation, based on a Mundlak-type specification, provides a surprisingly simple approach to efficient estimation and a straightforward way to assess the assumptions required. As an illustration, we combine unique information on the morbidity of Danish type 2 diabetes patients with information about GP clinics to investigate the association with fee-for-service healthcare expenditure. Our approach allows us to conclude that explanatory power is mainly provided by patient information and patient mix, whereas (possibly unobserved) clinic characteristics seem to play a minor role.

Suggested Citation

  • Bache, Stefan Holst Milton & Kristensen, Troels, 2013. "A simple but efficient approach to the analysis of multilevel data," DaCHE discussion papers 2013:6, University of Southern Denmark, Dache - Danish Centre for Health Economics.
  • Handle: RePEc:hhs:sduhec:2013_006
    as

    Download full text from publisher

    File URL: https://www.sdu.dk/-/media/files/om_sdu/centre/cohere/working+papers/2013/2013_6.pdf
    File Function: Full text
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Starfield, Barbara & Kinder, Karen, 2011. "Multimorbidity and its measurement," Health Policy, Elsevier, vol. 103(1), pages 3-8.
    2. Hausman, Jerry, 2015. "Specification tests in econometrics," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 38(2), pages 112-134.
    3. Laudicella, Mauro & Olsen, Kim Rose & Street, Andrew, 2010. "Examining cost variation across hospital departments-a two-stage multi-level approach using patient-level data," Social Science & Medicine, Elsevier, vol. 71(10), pages 1872-1881, November.
    4. Jason M. Fletcher, 2010. "Social interactions and smoking: evidence using multiple student cohorts, instrumental variables, and school fixed effects," Health Economics, John Wiley & Sons, Ltd., vol. 19(4), pages 466-484, April.
    5. Baltagi, Badi H., 2006. "An Alternative Derivation Of Mundlak'S Fixed Effects Results Using System Estimation," Econometric Theory, Cambridge University Press, vol. 22(6), pages 1191-1194, December.
    6. Lewis, Jeffrey B. & Linzer, Drew A., 2005. "Estimating Regression Models in Which the Dependent Variable Is Based on Estimates," Political Analysis, Cambridge University Press, vol. 13(4), pages 345-364.
    7. Richard Blundell & Frank Windmeijer, 1997. "Cluster effects and simultaneity in multilevel models," Health Economics, John Wiley & Sons, Ltd., vol. 6(4), pages 439-443, July.
    8. Nigel Rice & Andrew Jones, 1997. "Multilevel models and health economics," Health Economics, John Wiley & Sons, Ltd., vol. 6(6), pages 561-575, November.
    9. Mundlak, Yair, 1978. "On the Pooling of Time Series and Cross Section Data," Econometrica, Econometric Society, vol. 46(1), pages 69-85, January.
    10. Kathleen Carey, 2000. "A multilevel modelling approach to analysis of patient costs under managed care," Health Economics, John Wiley & Sons, Ltd., vol. 9(5), pages 435-446, July.
    Full references (including those not matched with items on IDEAS)

    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. Gemma Abio & Ció Patxot & Alexandrina Stoyanova & Raquel Andrés & Guadalupe Souto, 2022. "Lifecycle consumption and household structure: A pseudo-panel approach," UB School of Economics Working Papers 2022/436, University of Barcelona School of Economics.
    2. Aleksey Oshchepkov & Anna Shirokanova, 2020. "Multilevel Modeling For Economists: Why, When And How," HSE Working papers WP BRP 233/EC/2020, National Research University Higher School of Economics.
    3. Troels Kristensen & Kim Olsen & Henrik Schroll & Janus Thomsen & Anders Halling, 2014. "Association between fee-for-service expenditures and morbidity burden in primary care," The European Journal of Health Economics, Springer;Deutsche Gesellschaft für Gesundheitsökonomie (DGGÖ), vol. 15(6), pages 599-610, July.
    4. Nils Gutacker & Chris Bojke & Silvio Daidone & Nancy J. Devlin & David Parkin & Andrew Street, 2013. "Truly Inefficient Or Providing Better Quality Of Care? Analysing The Relationship Between Risk‐Adjusted Hospital Costs And Patients' Health Outcomes," Health Economics, John Wiley & Sons, Ltd., vol. 22(8), pages 931-947, August.
    5. Rabe-Hesketh, Sophia & Skrondal, Anders & Pickles, Andrew, 2005. "Maximum likelihood estimation of limited and discrete dependent variable models with nested random effects," Journal of Econometrics, Elsevier, vol. 128(2), pages 301-323, October.
    6. Yang, Yimin, 2022. "A correlated random effects approach to the estimation of models with multiple fixed effects," Economics Letters, Elsevier, vol. 213(C).
    7. Gianluca Fiorentini & Silvana Robone & Rossella Verzulli, 2018. "How do hospital‐specialty characteristics influence health system responsiveness? An empirical evaluation of in‐patient care in the Italian region of Emilia‐Romagna," Health Economics, John Wiley & Sons, Ltd., vol. 27(2), pages 266-281, February.
    8. A. Mahabbati & A. Izady & M. Mousavi Baygi & K. Davary & S. M. Hasheminia, 2017. "Daily soil temperature modeling using ‘panel-data’ concept," Journal of Applied Statistics, Taylor & Francis Journals, vol. 44(8), pages 1385-1401, June.
    9. Hadley, David, 1998. "Estimation Of Shadow Prices Of Undesirable Outputs: An Application To Uk Dairy Farms," 1998 Annual meeting, August 2-5, Salt Lake City, UT 20977, American Agricultural Economics Association (New Name 2008: Agricultural and Applied Economics Association).
    10. Arnd Kölling & Claus Schnabel, 2022. "Owners, external managers and industrial relations in German establishments," British Journal of Industrial Relations, London School of Economics, vol. 60(2), pages 424-443, June.
    11. Verbeek, M.J.C.M. & Nijman, T.E., 1992. "Incomplete panels and selection bias : A survey," Discussion Paper 1992-7, Tilburg University, Center for Economic Research.
    12. Nadjia Mehraban & Christoph Kubitza & Zulkifli Alamsyah & Matin Qaim, 2021. "Oil palm cultivation, household welfare, and exposure to economic risk in the Indonesian small farm sector," Journal of Agricultural Economics, Wiley Blackwell, vol. 72(3), pages 901-915, September.
    13. John Geweke & Joel Horowitz & M. Hashem Pesaran, 2006. "Econometrics: A Bird’s Eye View," CESifo Working Paper Series 1870, CESifo.
    14. Maggie Xiaoyang Chen & Aaditya Mattoo, 2008. "Regionalism in standards: good or bad for trade?," Canadian Journal of Economics, Canadian Economics Association, vol. 41(3), pages 838-863, August.
    15. Jones, Andrew M. & Wildman, John, 2008. "Health, income and relative deprivation: Evidence from the BHPS," Journal of Health Economics, Elsevier, vol. 27(2), pages 308-324, March.
    16. Shahrouz Abolhosseini & Almas Heshmati & Jorn Altmann, 2014. "The Effect of Renewable Energy Development on Carbon Emission Reduction: An Empirical Analysis for the EU-15 Countries," TEMEP Discussion Papers 2014109, Seoul National University; Technology Management, Economics, and Policy Program (TEMEP), revised Mar 2014.
    17. Hausman, Jerry A., 2003. "Triangular structural model specification and estimation with application to causality," Journal of Econometrics, Elsevier, vol. 112(1), pages 107-113, January.
    18. Le Hoang Phong, 2019. "Globalization, Financial Development, and Environmental Degradation in the Presence of Environmental Kuznets Curve: Evidence from ASEAN-5 Countries," International Journal of Energy Economics and Policy, Econjournals, vol. 9(2), pages 40-50.
    19. Subir Sen & S Madheswaran, 2013. "Regional determinants of life insurance consumption: evidence from selected Asian economies," Asian-Pacific Economic Literature, The Crawford School, The Australian National University, vol. 27(2), pages 86-103, November.
    20. Stern, David I. & Common, Michael S., 2001. "Is There an Environmental Kuznets Curve for Sulfur?," Journal of Environmental Economics and Management, Elsevier, vol. 41(2), pages 162-178, March.

    More about this item

    Keywords

    Multilevel models; random intercepts; nested models; Mundlak device; correlated random effects; 2-step estimation; estimated dependent variables; fee-for-service expenditures; type 2 diabetes;
    All these keywords.

    JEL classification:

    • C01 - Mathematical and Quantitative Methods - - General - - - Econometrics
    • C18 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Methodolical Issues: General
    • C38 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Classification Methdos; Cluster Analysis; Principal Components; Factor Analysis
    • H51 - Public Economics - - National Government Expenditures and Related Policies - - - Government Expenditures and Health
    • I18 - Health, Education, and Welfare - - Health - - - Government Policy; Regulation; Public Health

    NEP fields

    This paper has been announced in the following NEP Reports:

    Statistics

    Access and download statistics

    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:hhs:sduhec:2013_006. 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: Christian Volmar Skovsgaard (email available below). General contact details of provider: https://edirc.repec.org/data/hesdudk.html .

    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.