IDEAS home Printed from https://ideas.repec.org/a/bla/istatr/v85y2017i3p421-438.html
   My bibliography  Save this article

Variance Estimation of Imputed Estimators of Change for Repeated Rotating Surveys

Author

Listed:
  • Yves G. Berger
  • Emilio L. Escobar

Abstract

No abstract is available for this item.

Suggested Citation

  • Yves G. Berger & Emilio L. Escobar, 2017. "Variance Estimation of Imputed Estimators of Change for Repeated Rotating Surveys," International Statistical Review, International Statistical Institute, vol. 85(3), pages 421-438, December.
  • Handle: RePEc:bla:istatr:v:85:y:2017:i:3:p:421-438
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/10.1111/insr.12197
    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. Rebecca R. Andridge & Roderick J. A. Little, 2010. "A Review of Hot Deck Imputation for Survey Non‐response," International Statistical Review, International Statistical Institute, vol. 78(1), pages 40-64, April.
    2. Y. G. Berger & R. Priam, 2016. "A simple variance estimator of change for rotating repeated surveys: an application to the European Union Statistics on Income and Living Conditions household surveys," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 179(1), pages 251-272, January.
    3. David Haziza & Jean‐François Beaumont, 2007. "On the Construction of Imputation Classes in Surveys," International Statistical Review, International Statistical Institute, vol. 75(1), pages 25-43, April.
    4. C. Goga & J.-C. Deville & A. Ruiz-Gazen, 2009. "Use of functionals in linearization and composite estimation with application to two-sample survey data," Biometrika, Biometrika Trust, vol. 96(3), pages 691-709.
    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. Encarnación Álvarez-Verdejo & Pablo J. Moya-Fernández & Juan F. Muñoz-Rosas, 2021. "Single Imputation Methods and Confidence Intervals for the Gini Index," Mathematics, MDPI, vol. 9(24), pages 1-20, December.
    2. Raymundo M. Campos-Vázquez, 2013. "Efectos de los ingresos no reportados en el nivel y tendencia de la pobreza laboral en México," Ensayos Revista de Economia, Universidad Autonoma de Nuevo Leon, Facultad de Economia, vol. 0(2), pages 23-54, November.
    3. Paul T. von Hippel, 2013. "Should a Normal Imputation Model be Modified to Impute Skewed Variables?," Sociological Methods & Research, , vol. 42(1), pages 105-138, February.
    4. Meyer, Bruce D. & Mittag, Nikolas, 2019. "Combining Administrative and Survey Data to Improve Income Measurement," IZA Discussion Papers 12266, Institute of Labor Economics (IZA).
    5. Nancy, Jane Y. & Khanna, Nehemiah H. & Arputharaj, Kannan, 2017. "Imputing missing values in unevenly spaced clinical time series data to build an effective temporal classification framework," Computational Statistics & Data Analysis, Elsevier, vol. 112(C), pages 63-79.
    6. McDonough, Ian K. & Millimet, Daniel L., 2017. "Missing data, imputation, and endogeneity," Journal of Econometrics, Elsevier, vol. 199(2), pages 141-155.
    7. Marcello D’Orazio, 2015. "Integration and imputation of survey data in R: the StatMatch package," Romanian Statistical Review, Romanian Statistical Review, vol. 63(2), pages 57-68, June.
    8. Zhong, Hua & Hu, Wuyang, 2015. "Farmers’ Willingness to Engage in Best Management Practices: an Application of Multiple Imputation," 2015 Annual Meeting, January 31-February 3, 2015, Atlanta, Georgia 196962, Southern Agricultural Economics Association.
    9. Yanqing Sun & Li Qi & Fei Heng & Peter B. Gilbert, 2020. "A hybrid approach for the stratified mark‐specific proportional hazards model with missing covariates and missing marks, with application to vaccine efficacy trials," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 69(4), pages 791-814, August.
    10. Nathalie de Marcellis-Warin & Ingrid Peignier, 2021. "Perception des risques au Québec - Baromètre CIRANO 2021," CIRANO Papers 2021li-01, CIRANO.
    11. Thomas Masterson, 2012. "Simulations of Full-Time Employment and Household Work in the Levy Institute Measure of Time and Income Poverty (LIMTIP) for Argentina, Chile, and Mexico," Economics Working Paper Archive wp_727, Levy Economics Institute.
    12. Chiara Elena Dalla & Menon Martina & Perali Federico, 2019. "An Integrated Database to Measure Living Standards," Journal of Official Statistics, Sciendo, vol. 35(3), pages 531-576, September.
    13. Lidia Ceriani & Vladimir Hlasny & Paolo Verme, 2021. "Bottom Incomes and the Measurement of Poverty: A Brief Assessment of the Literature," Working Papers 589, ECINEQ, Society for the Study of Economic Inequality.
    14. Wang, Jianqiang C., 2012. "Sample distribution function based goodness-of-fit test for complex surveys," Computational Statistics & Data Analysis, Elsevier, vol. 56(3), pages 664-679.
    15. Nicklas Pettersson, 2013. "Bias reduction of finite population imputation by kernel methods," Statistics in Transition new series, Główny Urząd Statystyczny (Polska), vol. 14(1), pages 139-160, March.
    16. Daniel Araya & Guillermo Paraje, 2018. "The impact of prices on alcoholic beverage consumption in Chile," PLOS ONE, Public Library of Science, vol. 13(10), pages 1-15, October.
    17. Jeongsub Choi & Youngdoo Son & Myong K. Jeong, 2024. "Gaussian kernel with correlated variables for incomplete data," Annals of Operations Research, Springer, vol. 341(1), pages 223-244, October.
    18. Sullivan, Danielle & Andridge, Rebecca, 2015. "A hot deck imputation procedure for multiply imputing nonignorable missing data: The proxy pattern-mixture hot deck," Computational Statistics & Data Analysis, Elsevier, vol. 82(C), pages 173-185.
    19. Soyeon Ahn & John M. Abbamonte, 2020. "A new approach for handling missing correlation values for meta‐analytic structural equation modeling: Corboundary R package," Campbell Systematic Reviews, John Wiley & Sons, vol. 16(1), March.
    20. Cheng, Xiaoyue & Cook, Dianne & Hofmann, Heike, 2015. "Visually Exploring Missing Values in Multivariable Data Using a Graphical User Interface," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 68(i06).

    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:istatr:v:85:y:2017:i:3:p:421-438. 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/isiiinl.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.