IDEAS home Printed from https://ideas.repec.org/a/bla/biomet/v70y2014i1p44-52.html
   My bibliography  Save this article

Likelihood-based analysis of longitudinal data from outcome-related sampling designs

Author

Listed:
  • John M. Neuhaus
  • Alastair J. Scott
  • Christopher J. Wild
  • Yannan Jiang
  • Charles E. McCulloch
  • Ross Boylan

Abstract

No abstract is available for this item.

Suggested Citation

  • John M. Neuhaus & Alastair J. Scott & Christopher J. Wild & Yannan Jiang & Charles E. McCulloch & Ross Boylan, 2014. "Likelihood-based analysis of longitudinal data from outcome-related sampling designs," Biometrics, The International Biometric Society, vol. 70(1), pages 44-52, March.
  • Handle: RePEc:bla:biomet:v:70:y:2014:i:1:p:44-52
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/10.1111/biom.12108
    Download Restriction: Access to full text is restricted to subscribers.
    ---><---

    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. John M. Neuhaus & Charles E. McCulloch, 2006. "Separating between‐ and within‐cluster covariate effects by using conditional and partitioning methods," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 68(5), pages 859-872, November.
    2. Jonathan S. Schildcrout & Paul J. Rathouz, 2010. "Longitudinal Studies of Binary Response Data Following Case–Control and Stratified Case–Control Sampling: Design and Analysis," Biometrics, The International Biometric Society, vol. 66(2), pages 365-373, June.
    3. Alan Lee & Yuichi Hirose, 2010. "Semi-parametric efficiency bounds for regression models under response-selective sampling: the profile likelihood approach," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 62(6), pages 1023-1052, December.
    4. J. M. Neuhaus & A. J. Scott & C. J. Wild, 2006. "Family-Specific Approaches to the Analysis of Case–Control Family Data," Biometrics, The International Biometric Society, vol. 62(2), pages 488-494, June.
    5. J. Neuhaus, 2002. "The analysis of retrospective family studies," Biometrika, Biometrika Trust, vol. 89(1), pages 23-37, March.
    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. Sara Sauer & Bethany Hedt‐Gauthier & Claudia Rivera‐Rodriguez & Sebastien Haneuse, 2022. "Small‐sample inference for cluster‐based outcome‐dependent sampling schemes in resource‐limited settings: Investigating low birthweight in Rwanda," Biometrics, The International Biometric Society, vol. 78(2), pages 701-715, June.
    2. Glen McGee & Marianthi‐Anna Kioumourtzoglou & Marc G. Weisskopf & Sebastien Haneuse & Brent A. Coull, 2020. "On the interplay between exposure misclassification and informative cluster size," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 69(5), pages 1209-1226, November.
    3. Glen McGee & Jonathan Schildcrout & Sharon‐Lise Normand & Sebastien Haneuse, 2020. "Outcome‐dependent sampling in cluster‐correlated data settings with application to hospital profiling," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 183(1), pages 379-402, January.

    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. Jonathan S. Schildcrout & Shawn P. Garbett & Patrick J. Heagerty, 2013. "Outcome Vector Dependent Sampling with Longitudinal Continuous Response Data: Stratified Sampling Based on Summary Statistics," Biometrics, The International Biometric Society, vol. 69(2), pages 405-416, June.
    2. Glen McGee & Jonathan Schildcrout & Sharon‐Lise Normand & Sebastien Haneuse, 2020. "Outcome‐dependent sampling in cluster‐correlated data settings with application to hospital profiling," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 183(1), pages 379-402, January.
    3. Yingye Zheng & Patrick J. Heagerty & Li Hsu & Polly A. Newcomb, 2010. "On Combining Family-Based and Population-Based Case–Control Data in Association Studies," Biometrics, The International Biometric Society, vol. 66(4), pages 1024-1033, December.
    4. Jonathan S. Schildcrout & Patrick J. Heagerty, 2011. "Outcome-Dependent Sampling from Existing Cohorts with Longitudinal Binary Response Data: Study Planning and Analysis," Biometrics, The International Biometric Society, vol. 67(4), pages 1583-1593, December.
    5. Glen McGee & Marianthi‐Anna Kioumourtzoglou & Marc G. Weisskopf & Sebastien Haneuse & Brent A. Coull, 2020. "On the interplay between exposure misclassification and informative cluster size," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 69(5), pages 1209-1226, November.
    6. Jonathan S. Schildcrout & Paul J. Rathouz, 2010. "Longitudinal Studies of Binary Response Data Following Case–Control and Stratified Case–Control Sampling: Design and Analysis," Biometrics, The International Biometric Society, vol. 66(2), pages 365-373, June.
    7. Quinn N. Lathrop & Ying Cheng, 2017. "Item Cloning Variation and the Impact on the Parameters of Response Models," Psychometrika, Springer;The Psychometric Society, vol. 82(1), pages 245-263, March.
    8. Marco Alfò & Lorenzo Carbonari & Giovanni Trovato, 2020. "On the Effects of Taxation on Growth: an Empirical Assessment," CEIS Research Paper 480, Tor Vergata University, CEIS, revised 08 May 2020.
    9. Ying Huang & Brian Leroux, 2011. "Informative Cluster Sizes for Subcluster-Level Covariates and Weighted Generalized Estimating Equations," Biometrics, The International Biometric Society, vol. 67(3), pages 843-851, September.
    10. J. M. Neuhaus & A. J. Scott & C. J. Wild, 2006. "Family-Specific Approaches to the Analysis of Case–Control Family Data," Biometrics, The International Biometric Society, vol. 62(2), pages 488-494, June.
    11. Judith Clarke & Nilanjana Roy & Marsha Courchane, 2009. "On the robustness of racial discrimination findings in mortgage lending studies," Applied Economics, Taylor & Francis Journals, vol. 41(18), pages 2279-2297.
    12. Ullah, Inayat & Hussain, Saqib, 2023. "Impact of early access to land record information through digitization: Evidence from Alternate Dispute Resolution Data in Punjab, Pakistan," Land Use Policy, Elsevier, vol. 134(C).
    13. Brent A Coull, 2011. "A Random Intercepts–Functional Slopes Model for Flexible Assessment of Susceptibility in Longitudinal Designs," Biometrics, The International Biometric Society, vol. 67(2), pages 486-494, June.
    14. Seonho Shin, 2021. "Were they a shock or an opportunity?: The heterogeneous impacts of the 9/11 attacks on refugees as job seekers—a nonlinear multi-level approach," Empirical Economics, Springer, vol. 61(5), pages 2827-2864, November.
    15. Tanya P. Garcia & Yanyuan Ma, 2016. "Optimal Estimator for Logistic Model with Distribution-free Random Intercept," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 43(1), pages 156-171, March.
    16. Andrew Bell & Malcolm Fairbrother & Kelvyn Jones, 2019. "Fixed and random effects models: making an informed choice," Quality & Quantity: International Journal of Methodology, Springer, vol. 53(2), pages 1051-1074, March.
    17. Krieg Sabine & Boonstra Harm Jan & Smeets Marc, 2016. "Small-Area Estimation with Zero-Inflated Data – a Simulation Study," Journal of Official Statistics, Sciendo, vol. 32(4), pages 963-986, December.
    18. Sylvie Goetgeluk & Stijn Vansteelandt, 2008. "Conditional Generalized Estimating Equations for the Analysis of Clustered and Longitudinal Data," Biometrics, The International Biometric Society, vol. 64(3), pages 772-780, September.
    19. Anders Skrondal & Sophia Rabe-Hesketh, 2022. "The Role of Conditional Likelihoods in Latent Variable Modeling," Psychometrika, Springer;The Psychometric Society, vol. 87(3), pages 799-834, September.
    20. Brumback, Babette A. & Dailey, Amy B. & Brumback, Lyndia C. & Livingston, Melvin D. & He, Zhulin, 2010. "Adjusting for confounding by cluster using generalized linear mixed models," Statistics & Probability Letters, Elsevier, vol. 80(21-22), pages 1650-1654, November.

    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:biomet:v:70:y:2014:i:1:p:44-52. 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: http://www.blackwellpublishing.com/journal.asp?ref=0006-341X .

    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.