IDEAS home Printed from https://ideas.repec.org/a/eee/csdana/v51y2007i8p3898-3912.html

A smoothed residual based goodness-of-fit statistic for logistic hierarchical regression models

Author

Listed:
  • Sturdivant, Rodney X.
  • Hosmer Jr., David W.

Abstract

No abstract is available for this item.

Suggested Citation

  • Sturdivant, Rodney X. & Hosmer Jr., David W., 2007. "A smoothed residual based goodness-of-fit statistic for logistic hierarchical regression models," Computational Statistics & Data Analysis, Elsevier, vol. 51(8), pages 3898-3912, May.
  • Handle: RePEc:eee:csdana:v:51:y:2007:i:8:p:3898-3912
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0167-9473(06)00079-X
    Download Restriction: Full text for ScienceDirect subscribers only.
    ---><---

    As the access to this document is restricted, you may want to

    for a different version of it.

    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. J. B. Copas, 1989. "Unweighted Sum of Squares Test for Proportions," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 38(1), pages 71-80, March.
    3. Germáan Rodríguez & Noreen Goldman, 1995. "An Assessment of Estimation Procedures for Multilevel Models with Binary Responses," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 158(1), pages 73-89, January.
    4. Hardle, Wolfgang & Linton, Oliver, 1986. "Applied nonparametric methods," Handbook of Econometrics, in: R. F. Engle & D. McFadden (ed.), Handbook of Econometrics, edition 1, volume 4, chapter 38, pages 2295-2339, Elsevier.
    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. 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.
    2. Chun Wang & Steven W. Nydick, 2020. "On Longitudinal Item Response Theory Models: A Didactic," Journal of Educational and Behavioral Statistics, , vol. 45(3), pages 339-368, June.
    3. An, Xinming & Bentler, Peter M., 2012. "Efficient direct sampling MCEM algorithm for latent variable models with binary responses," Computational Statistics & Data Analysis, Elsevier, vol. 56(2), pages 231-244.
    4. Chiara Masci & Francesca Ieva & Anna Maria Paganoni, 2024. "Inferential Tools for Assessing Dependence Across Response Categories in Multinomial Models with Discrete Random Effects," Journal of Classification, Springer;The Classification Society, vol. 41(3), pages 591-619, November.
    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. Cho, S.-J. & Rabe-Hesketh, S., 2011. "Alternating imputation posterior estimation of models with crossed random effects," Computational Statistics & Data Analysis, Elsevier, vol. 55(1), pages 12-25, January.
    7. Courgeau, Daniel, 2007. "Multilevel synthesis. From the group to the individual," MPRA Paper 43189, University Library of Munich, Germany.
    8. Sun-Joo Cho & Paul Boeck & Susan Embretson & Sophia Rabe-Hesketh, 2014. "Additive Multilevel Item Structure Models with Random Residuals: Item Modeling for Explanation and Item Generation," Psychometrika, Springer;The Psychometric Society, vol. 79(1), pages 84-104, January.
    9. Ziwen Ling & Christopher R. Cherry & Yi Wen, 2021. "Determining the Factors That Influence Electric Vehicle Adoption: A Stated Preference Survey Study in Beijing, China," Sustainability, MDPI, vol. 13(21), pages 1-22, October.
    10. Sun-Joo Cho & Jennifer Gilbert & Amanda Goodwin, 2013. "Explanatory Multidimensional Multilevel Random Item Response Model: An Application to Simultaneous Investigation of Word and Person Contributions to Multidimensional Lexical Representations," Psychometrika, Springer;The Psychometric Society, vol. 78(4), pages 830-855, October.
    11. Mirjam Moerbeek & Gerard J. P. Breukelen & Martijn P. F. Berger, 2003. "A Comparison of Estimation Methods for Multilevel Logistic Models," Computational Statistics, Springer, vol. 18(1), pages 19-37, March.
    12. 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).
    13. Dabo-Niang, Sophie & Francq, Christian & Zakoïan, Jean-Michel, 2010. "Combining Nonparametric and Optimal Linear Time Series Predictions," Journal of the American Statistical Association, American Statistical Association, vol. 105(492), pages 1554-1565.
    14. Koop, Gary & Poirier, Dale J., 2004. "Bayesian variants of some classical semiparametric regression techniques," Journal of Econometrics, Elsevier, vol. 123(2), pages 259-282, December.
    15. Anoop Jain & Rockli Kim & S V Subramanian, 2025. "Analyzing changes in types of household sanitation among 543 Parliamentary Constituencies between 2016 and 2021 in India," PLOS Water, Public Library of Science, vol. 4(8), pages 1-13, August.
    16. 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.
    17. Creemers, An & Aerts, Marc & Hens, Niel & Molenberghs, Geert, 2012. "A nonparametric approach to weighted estimating equations for regression analysis with missing covariates," Computational Statistics & Data Analysis, Elsevier, vol. 56(1), pages 100-113, January.
    18. Néstor Duch-Brown & José García-Quevedo & Daniel Montolio, 2011. "The link between public support and private R&D effort: What is the optimal subsidy?," Working Papers XREAP2011-09, Xarxa de Referència en Economia Aplicada (XREAP), revised Jun 2011.
    19. Austan Goolsbee & David B. Gross, 1997. "Estimating Adjustment Costs with Data on Heterogeneous Capital Goods," NBER Working Papers 6342, National Bureau of Economic Research, Inc.
    20. Douglas J. Hodgson & Oliver Linton & Keith Vorkink, 2002. "Testing the capital asset pricing model efficiently under elliptical symmetry: a semiparametric approach," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 17(6), pages 617-639, December.

    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:eee:csdana:v:51:y:2007:i:8:p:3898-3912. 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/locate/csda .

    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.