IDEAS home Printed from https://ideas.repec.org/a/bla/biomet/v63y2007i4p1172-1180.html
   My bibliography  Save this article

Parametric and Semiparametric Model-Based Estimates of the Finite Population Mean for Two-Stage Cluster Samples with Item Nonresponse

Author

Listed:
  • Ying Yuan
  • Roderick J. A. Little

Abstract

No abstract is available for this item.

Suggested Citation

  • Ying Yuan & Roderick J. A. Little, 2007. "Parametric and Semiparametric Model-Based Estimates of the Finite Population Mean for Two-Stage Cluster Samples with Item Nonresponse," Biometrics, The International Biometric Society, vol. 63(4), pages 1172-1180, December.
  • Handle: RePEc:bla:biomet:v:63:y:2007:i:4:p:1172-1180
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/10.1111/j.1541-0420.2007.00816.x
    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. Ying Yuan & Roderick J. A. Little, 2007. "Model‐based estimates of the finite population mean for two‐stage cluster samples with unit non‐response," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 56(1), pages 79-97, January.
    2. Little R.J., 2004. "To Model or Not To Model? Competing Modes of Inference for Finite Population Sampling," Journal of the American Statistical Association, American Statistical Association, vol. 99, pages 546-556, January.
    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. Ying Yuan & Roderick J. A. Little, 2009. "Meta-Analysis of Studies with Missing Data," Biometrics, The International Biometric Society, vol. 65(2), pages 487-496, June.
    2. Nuanpan Lawson & Chris Skinner, 2017. "Estimation of a cluster-level regression model under nonresponse within clusters," METRON, Springer;Sapienza Università di Roma, vol. 75(3), pages 319-331, December.
    3. Jouni Kuha & Myrsini Katsikatsou & Irini Moustaki, 2018. "Latent variable modelling with non‐ignorable item non‐response: multigroup response propensity models for cross‐national analysis," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 181(4), pages 1169-1192, October.
    4. Kim, Gi-Soo & Paik, Myunghee Cho & Kim, Hongsoo, 2017. "Causal inference with observational data under cluster-specific non-ignorable assignment mechanism," Computational Statistics & Data Analysis, Elsevier, vol. 113(C), pages 88-99.
    5. Zhou Hanzhi & Elliott Michael R. & Raghunathan Trivellore E., 2016. "Synthetic Multiple-Imputation Procedure for Multistage Complex Samples," Journal of Official Statistics, Sciendo, vol. 32(1), pages 231-256, March.

    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. Little Roderick J., 2013. "Discussion," Journal of Official Statistics, Sciendo, vol. 29(3), pages 363-366, June.
    2. Kunihama, T. & Herring, A.H. & Halpern, C.T. & Dunson, D.B., 2016. "Nonparametric Bayes modeling with sample survey weights," Statistics & Probability Letters, Elsevier, vol. 113(C), pages 41-48.
    3. Marivoet, Wim & De Herdt, Tom, 2017. "From figures to facts: making sense of socio-economic surveys in the Democratic Republic of the Congo (DRC)," IOB Analyses & Policy Briefs 23, Universiteit Antwerpen, Institute of Development Policy (IOB).
    4. Geoffrey Jones & Wesley O. Johnson, 2016. "A Bayesian Superpopulation Approach to Inference for Finite Populations Based on Imperfect Diagnostic Outcomes," Journal of Agricultural, Biological and Environmental Statistics, Springer;The International Biometric Society;American Statistical Association, vol. 21(2), pages 314-327, June.
    5. J. Andrew Royle, 2009. "Analysis of Capture–Recapture Models with Individual Covariates Using Data Augmentation," Biometrics, The International Biometric Society, vol. 65(1), pages 267-274, March.
    6. Jouni Kuha & Myrsini Katsikatsou & Irini Moustaki, 2018. "Latent variable modelling with non‐ignorable item non‐response: multigroup response propensity models for cross‐national analysis," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 181(4), pages 1169-1192, October.
    7. David Kaplan & Chansoon Lee, 2018. "Optimizing Prediction Using Bayesian Model Averaging: Examples Using Large-Scale Educational Assessments," Evaluation Review, , vol. 42(4), pages 423-457, August.
    8. Bijak Jakub & Bryant Johan & Gołata Elżbieta & Smallwood Steve, 2021. "Preface," Journal of Official Statistics, Sciendo, vol. 37(3), pages 533-541, September.
    9. Parcel Joshua D. & Schroeter John R. & Azzam Azzeddine M, 2017. "A Re-Examination of Multistage Economies in Hog Farming," Journal of Agricultural & Food Industrial Organization, De Gruyter, vol. 15(2), pages 1-15, December.
    10. Ralf Münnich & Siegfried Gabler & Christian Bruch & Jan Pablo Burgard & Tobias Enderle & Jan-Philipp Kolb & Thomas Zimmermann, 2015. "Tabellenauswertungen im Zensus unter Berücksichtigung fehlender Werte," AStA Wirtschafts- und Sozialstatistisches Archiv, Springer;Deutsche Statistische Gesellschaft - German Statistical Society, vol. 9(3), pages 269-304, December.
    11. Sahar Z. Zangeneh & Roderick J. Little, 2022. "Likelihood‐Based Inference for the Finite Population Mean with Post‐Stratification Information Under Non‐Ignorable Non‐Response," International Statistical Review, International Statistical Institute, vol. 90(S1), pages 17-36, December.
    12. Shira Mitchell & Andrew Gelman & Rebecca Ross & Joyce Chen & Sehrish Bari & Uyen Kim Huynh & Matthew W. Harris & Sonia Ehrlich Sachs & Elizabeth A. Stuart & Avi Feller & Susanna Makela & Alan M. Zasla, "undated". "The Millennium Villages Project: A Retrospective, Observational, Endline Evaluation," Mathematica Policy Research Reports 8376cf28448b40f69543be760, Mathematica Policy Research.
    13. Tenan, Simone & Rotger Vallespir, Andreu & Igual, José Manuel & Moya, Óscar & Royle, J. Andrew & Tavecchia, Giacomo, 2013. "Population abundance, size structure and sex-ratio in an insular lizard," Ecological Modelling, Elsevier, vol. 267(C), pages 39-47.
    14. West Brady T. & Sakshaug Joseph W. & Aurelien Guy Alain S., 2018. "Accounting for Complex Sampling in Survey Estimation: A Review of Current Software Tools," Journal of Official Statistics, Sciendo, vol. 34(3), pages 721-752, September.
    15. Shixiao Zhang & Peisong Han & Changbao Wu, 2023. "Calibration Techniques Encompassing Survey Sampling, Missing Data Analysis and Causal Inference," International Statistical Review, International Statistical Institute, vol. 91(2), pages 165-192, August.
    16. Hwanhee Hong & Kara E. Rudolph & Elizabeth A. Stuart, 2017. "Bayesian Approach for Addressing Differential Covariate Measurement Error in Propensity Score Methods," Psychometrika, Springer;The Psychometric Society, vol. 82(4), pages 1078-1096, December.
    17. Geoffrey Jones & Wesley O. Johnson, 2014. "Prior Elicitation: Interactive Spreadsheet Graphics With Sliders Can Be Fun, and Informative," The American Statistician, Taylor & Francis Journals, vol. 68(1), pages 42-51, February.
    18. Robert M. Groves & Steven G. Heeringa, 2006. "Responsive design for household surveys: tools for actively controlling survey errors and costs," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 169(3), pages 439-457, July.
    19. Lukachko, Alicia & Hatzenbuehler, Mark L. & Keyes, Katherine M., 2014. "Structural racism and myocardial infarction in the United States," Social Science & Medicine, Elsevier, vol. 103(C), pages 42-50.
    20. Kim, Gi-Soo & Paik, Myunghee Cho & Kim, Hongsoo, 2017. "Causal inference with observational data under cluster-specific non-ignorable assignment mechanism," Computational Statistics & Data Analysis, Elsevier, vol. 113(C), pages 88-99.

    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:63:y:2007:i:4:p:1172-1180. 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.