IDEAS home Printed from https://ideas.repec.org/a/spr/stmapp/v16y2007i1p51-67.html
   My bibliography  Save this article

Robustness of Parameter Estimation Procedures in Multilevel Models When Random Effects are MEP Distributed

Author

Listed:
  • Nadia Solaro
  • Pier Ferrari

Abstract

In this paper we examine maximum likelihood estimation procedures in multilevel models for two level nesting structures. Usually, for fixed effects and variance components estimation, level-one error terms and random effects are assumed to be normally distributed. Nevertheless, in some circumstances this assumption might not be realistic, especially as concerns random effects. Thus we assume for random effects the family of multivariate exponential power distributions (MEP); subsequently, by means of Monte Carlo simulation procedures, we study robustness of maximum likelihood estimators under normal assumption when, actually, random effects are MEP distributed.
(This abstract was borrowed from another version of this item.)

Suggested Citation

  • Nadia Solaro & Pier Ferrari, 2007. "Robustness of Parameter Estimation Procedures in Multilevel Models When Random Effects are MEP Distributed," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 16(1), pages 51-67, June.
    • Handle: RePEc:spr:stmapp:v:16:y:2007:i:1:p:51-67
    DOI: 10.1007/s10260-006-0016-6
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/10.1007/s10260-006-0016-6
    Download Restriction: Access to full text is restricted to subscribers.
    File URL: https://libkey.io/10.1007/s10260-006-0016-6?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 look for a different version below or search for a different version of it.

    Other versions of this item:

    References listed on IDEAS

    as
    1. Lindsey, J. K., 1999. "Models for Repeated Measurements," OUP Catalogue, Oxford University Press, edition 2, number 9780198505594.
    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. Ho-Chul Park & Yang-Jun Joo & Seung-Young Kho & Dong-Kyu Kim & Byung-Jung Park, 2019. "Injury Severity of Bus–Pedestrian Crashes in South Korea Considering the Effects of Regional and Company Factors," Sustainability, MDPI, vol. 11(11), pages 1-17, June.

    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. Gianni Betti & Antonella D’Agostino & Laura Neri, 2002. "Panel regression models for measuring multidimensional poverty dynamics," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 11(3), pages 359-369, October.
    2. Ulf Böckenholt, 2003. "Analysing state dependences in emotional experiences by dynamic count data models," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 52(2), pages 213-226, May.
    3. P. J. Lindsey & J. Kaufmann, 2004. "Analysis of a longitudinal ordinal response clinical trial using dynamic models," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 53(3), pages 523-537, August.
    4. Merlo, Luca & Petrella, Lea & Salvati, Nicola & Tzavidis, Nikos, 2022. "Marginal M-quantile regression for multivariate dependent data," Computational Statistics & Data Analysis, Elsevier, vol. 173(C).
    5. Devin S. Johnson & Jennifer A. Hoeting, 2003. "Autoregressive Models for Capture-Recapture Data: A Bayesian Approach," Biometrics, The International Biometric Society, vol. 59(2), pages 341-350, June.
    6. Marta Nai Ruscone & Daniel Fernández, 2021. "Dynamics of HDI Index: Temporal Dependence Based on D-vine Copulas Model for Three-Way Data," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 158(2), pages 563-593, December.
    7. Ivy Liu & Alan Agresti, 2005. "The analysis of ordered categorical data: An overview and a survey of recent developments," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 14(1), pages 1-73, June.
    8. A. Azarbar & Y. Zhang & S. Nadarajah, 2019. "An investigation of effective factors on children’s growth failure in Iran using multilevel models," Quality & Quantity: International Journal of Methodology, Springer, vol. 53(2), pages 553-560, March.
    9. D. M. Farewell & C. Huang & V. Didelez, 2017. "Ignorability for general longitudinal data," Biometrika, Biometrika Trust, vol. 104(2), pages 317-326.
    10. Luca Merlo & Lea Petrella & Nikos Tzavidis, 2022. "Quantile mixed hidden Markov models for multivariate longitudinal data: An application to children's Strengths and Difficulties Questionnaire scores," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 71(2), pages 417-448, March.
    11. Mohsen Pourahmadi, 2002. "Graphical Diagnostics for Modeling Unstructured Covariance Matrices," International Statistical Review, International Statistical Institute, vol. 70(3), pages 395-417, December.
    12. Courgeau, Daniel, 2007. "Multilevel synthesis. From the group to the individual," MPRA Paper 43189, University Library of Munich, Germany.
    13. Lindsey, J.K. & Lindsey, P.J., 2006. "Multivariate distributions with correlation matrices for nonlinear repeated measurements," Computational Statistics & Data Analysis, Elsevier, vol. 50(3), pages 720-732, February.
    14. M. Pourahmadi & M. J. Daniels, 2002. "Dynamic Conditionally Linear Mixed Models for Longitudinal Data," Biometrics, The International Biometric Society, vol. 58(1), pages 225-231, March.
    15. Filomena Maggino & Carolina Facioni, 2017. "Measuring Stability and Change: Methodological Issues in Quality of Life studies," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 130(1), pages 161-187, January.
    16. Susanne May & Victor DeGruttola, 2007. "Nonparametric Tests for Two-Group Comparisons of Dependent Observations Obtained at Varying Time Points," Biometrics, The International Biometric Society, vol. 63(1), pages 194-200, March.

    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:stmapp:v:16:y:2007:i:1:p:51-67. 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.