IDEAS home Printed from https://ideas.repec.org/a/bla/jorssa/v185y2022i3p753-758.html
   My bibliography  Save this article

A celebration of Harvey Goldstein’s lifetime contributions: Memories of working with Harvey Goldstein on multilevel modelling methods and applications

Author

Listed:
  • William J. Browne

Abstract

No abstract is available for this item.

Suggested Citation

  • William J. Browne, 2022. "A celebration of Harvey Goldstein’s lifetime contributions: Memories of working with Harvey Goldstein on multilevel modelling methods and applications," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 185(3), pages 753-758, July.
  • Handle: RePEc:bla:jorssa:v:185:y:2022:i:3:p:753-758
    DOI: 10.1111/rssa.12898
    as

    Download full text from publisher

    File URL: https://doi.org/10.1111/rssa.12898
    Download Restriction: no

    File URL: https://libkey.io/10.1111/rssa.12898?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
    ---><---

    References listed on IDEAS

    as
    1. Harvey Goldstein & Jon Rasbash, 1996. "Improved Approximations for Multilevel Models with Binary Responses," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 159(3), pages 505-513, May.
    2. M. Yang & H. Goldstein & A. Heath, 2000. "Multilevel models for repeated binary outcomes: attitudes and voting over the electoral cycle," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 163(1), pages 49-62.
    3. Min Yang & Harvey Goldstein & William Browne & Geoffrey Woodhouse, 2002. "Multivariate multilevel analyses of examination results," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 165(1), pages 137-153, February.
    4. Harvey Goldstein & Min Yang & Rumana Omar & Rebecca Turner & Simon Thompson, 2000. "Meta‐analysis using multilevel models with an application to the study of class size effects," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 49(3), pages 399-412.
    5. Browne, William J. & Draper, David & Goldstein, Harvey & Rasbash, Jon, 2002. "Bayesian and likelihood methods for fitting multilevel models with complex level-1 variation," Computational Statistics & Data Analysis, Elsevier, vol. 39(2), pages 203-225, April.
    6. William Browne & Harvey Goldstein, 2010. "MCMC Sampling for a Multilevel Model With Nonindependent Residuals Within and Between Cluster Units," Journal of Educational and Behavioral Statistics, , vol. 35(4), pages 453-473, August.
    7. W. J. Browne & S. V. Subramanian & K. Jones & H. Goldstein, 2005. "Variance partitioning in multilevel logistic models that exhibit overdispersion," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 168(3), pages 599-613, July.
    8. Harvey Goldstein & James R. Carpenter & William J. Browne, 2014. "Fitting multilevel multivariate models with missing data in responses and covariates that may include interactions and non-linear terms," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 177(2), pages 553-564, February.
    9. Harvey Goldstein & William J. Browne & Christopher Charlton, 2018. "A Bayesian model for measurement and misclassification errors alongside missing data, with an application to higher education participation in Australia," Journal of Applied Statistics, Taylor & Francis Journals, vol. 45(5), pages 918-931, April.
    10. Harvey Goldstein & Jon Rasbash & William Browne & Geoffrey Woodhouse & Michel Poulain, 2000. "Multilevel Models in the Study of Dynamic Household Structures," European Journal of Population, Springer;European Association for Population Studies, vol. 16(4), pages 373-387, December.
    11. Harvey Goldstein & David J. Spiegelhalter, 1996. "League Tables and Their Limitations: Statistical Issues in Comparisons of Institutional Performance," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 159(3), pages 385-409, May.
    12. Geoffrey Woodhouse & Min Yang & Harvey Goldstein & Jon Rasbash, 1996. "Adjusting for Measurement Error in Multilevel Analysis," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 159(2), pages 201-212, March.
    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. Georges Kone & Richard Lalou & Martine Audibert & Hervé Lafarge & Stéphanie dos Santos & Jean-Yves Le Hesran, 2013. "Use of health care among the urban poor in Africa: Does the neighbourhood have an impact?," CERDI Working papers halshs-00878946, HAL.
    2. Li Mingliang & Tobias Justin, 2005. "Bayesian Modeling of School Effects Using Hierarchical Models with Smoothing Priors," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 9(3), pages 1-33, September.
    3. Brandon LeBeau & Yoon Ah Song & Wei Cheng Liu, 2018. "Model Misspecification and Assumption Violations With the Linear Mixed Model: A Meta-Analysis," SAGE Open, , vol. 8(4), pages 21582440188, December.
    4. George Leckie, 2022. "A celebration of Harvey Goldstein’s lifetime contributions: Memories of working with Harvey Goldstein on educational research and statistics," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 185(3), pages 758-762, July.
    5. David Cutts & Edward Fieldhouse, 2009. "What Small Spatial Scales Are Relevant as Electoral Contexts for Individual Voters? The Importance of the Household on Turnout at the 2001 General Election," American Journal of Political Science, John Wiley & Sons, vol. 53(3), pages 726-739, July.
    6. Stephen Jivraj, 2012. "Modelling Socioeconomic Neighbourhood Change due to Internal Migration in England," Urban Studies, Urban Studies Journal Limited, vol. 49(16), pages 3565-3578, December.
    7. Paul Hewson & Keming Yu, 2008. "Quantile regression for binary performance indicators," Applied Stochastic Models in Business and Industry, John Wiley & Sons, vol. 24(5), pages 401-418, September.
    8. Gabriele B. Durrant & Sylke V. Schnepf, 2018. "Which schools and pupils respond to educational achievement surveys?: a focus on the English Programme for International Student Assessment sample," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 181(4), pages 1057-1075, October.
    9. Elias Giannakis & Sophia Efstratoglou & Artemis Antoniades, 2018. "Off-Farm Employment and Economic Crisis: Evidence from Cyprus," Agriculture, MDPI, vol. 8(3), pages 1-11, March.
    10. Subramanian, S.V. & Elwert, Felix & Christakis, Nicholas, 2008. "Widowhood and mortality among the elderly: The modifying role of neighborhood concentration of widowed individuals," Social Science & Medicine, Elsevier, vol. 66(4), pages 873-884, February.
    11. Bellelli, Francesco S. & Scarpa, Riccardo & Aftab, Ashar, 2023. "An empirical analysis of participation in international environmental agreements," Journal of Environmental Economics and Management, Elsevier, vol. 118(C).
    12. Bornmann, Lutz & Leydesdorff, Loet & Wang, Jian, 2014. "How to improve the prediction based on citation impact percentiles for years shortly after the publication date?," Journal of Informetrics, Elsevier, vol. 8(1), pages 175-180.
    13. Subramanian, S.V. & Acevedo-Garcia, Dolores & Osypuk, Theresa L., 2005. "Racial residential segregation and geographic heterogeneity in black/white disparity in poor self-rated health in the US: a multilevel statistical analysis," Social Science & Medicine, Elsevier, vol. 60(8), pages 1667-1679, April.
    14. Arpino, Bruno & Varriale, Roberta, 2009. "Assessing the quality of institutions’ rankings obtained through multilevel linear regression models," MPRA Paper 19873, University Library of Munich, Germany.
    15. Renard, Didier & Molenberghs, Geert & Geys, Helena, 2004. "A pairwise likelihood approach to estimation in multilevel probit models," Computational Statistics & Data Analysis, Elsevier, vol. 44(4), pages 649-667, January.
    16. Kelvyn Jones & David Manley & Ron Johnston & Dewi Owen, 2018. "Modelling residential segregation as unevenness and clustering: A multilevel modelling approach incorporating spatial dependence and tackling the MAUP," Environment and Planning B, , vol. 45(6), pages 1122-1141, November.
    17. Mutz, Rüdiger & Daniel, Hans-Dieter, 2018. "The bibliometric quotient (BQ), or how to measure a researcher’s performance capacity: A Bayesian Poisson Rasch model," Journal of Informetrics, Elsevier, vol. 12(4), pages 1282-1295.
    18. Magne Mogstad & Joseph P Romano & Azeem M Shaikh & Daniel Wilhelm, 2024. "Inference for Ranks with Applications to Mobility across Neighbourhoods and Academic Achievement across Countries," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 91(1), pages 476-518.
    19. Daraio, Cinzia & Bonaccorsi, Andrea & Simar, Léopold, 2015. "Rankings and university performance: A conditional multidimensional approach," European Journal of Operational Research, Elsevier, vol. 244(3), pages 918-930.
    20. repec:lan:wpaper:991 is not listed on IDEAS
    21. Mindlis, Irina & Livert, David & Federman, Alex D. & Wisnivesky, Juan P. & Revenson, Tracey A., 2020. "Racial/ethnic concordance between patients and researchers as a predictor of study attrition," Social Science & Medicine, Elsevier, vol. 255(C).

    More about this item

    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:bla:jorssa:v:185:y:2022:i:3:p:753-758. 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: Wiley Content Delivery (email available below). General contact details of provider: https://edirc.repec.org/data/rssssea.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.