IDEAS home Printed from https://ideas.repec.org/a/eee/stapro/v58y2002i3p221-232.html
   My bibliography  Save this article

Survival estimation and testing via multiple imputation

Author

Listed:
  • Taylor, Jeremy M. G.
  • Murray, Susan
  • Hsu, Chiu-Hsieh

Abstract

Multiple imputation is a technique for handling data sets with missing values. The method fills in each missing value several times, creating many augmented data sets. Each augmented data set is analyzed separately and the results combined to give a final result consisting of an estimate and a measure of uncertainty. In this paper we consider nonparametric multiple-imputation methods to handle missing event times for censored observations in the context of nonparametric survival estimation and testing. Two nonparametric imputation schemes are considered. In risk set imputation the censored time is replaced by a random draw of the observed times amongst those at risk after the censoring time. In Kaplan-Meier (KM) imputation the imputed time is a draw from the estimated distribution of event times amongst those at risk after the censoring time. We show that with a large number of imputes the estimates from both methods reproduce the KM estimator. In a simulation study we show that the inclusion of a bootstrap stage in the multiple imputation algorithm gives coverage rates of confidence intervals that are comparable to that from Greenwood's formula. Connections to the redistribute to the right algorithm are discussed.

Suggested Citation

  • Taylor, Jeremy M. G. & Murray, Susan & Hsu, Chiu-Hsieh, 2002. "Survival estimation and testing via multiple imputation," Statistics & Probability Letters, Elsevier, vol. 58(3), pages 221-232, July.
    • Handle: RePEc:eee:stapro:v:58:y:2002:i:3:p:221-232
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0167-7152(02)00030-5
    Download Restriction: Full text for ScienceDirect subscribers only
    ---><---

    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. Schenker, Nathaniel & Taylor, Jeremy M. G., 1996. "Partially parametric techniques for multiple imputation," Computational Statistics & Data Analysis, Elsevier, vol. 22(4), pages 425-446, August.
    2. Daniel F. Heitjan & Roderick J. A. Little, 1991. "Multiple Imputation for the Fatal Accident Reporting System," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 40(1), pages 13-29, 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. Shirin Moghaddam & John Newell & John Hinde, 2022. "A Bayesian Approach for Imputation of Censored Survival Data," Stats, MDPI, vol. 5(1), pages 1-19, January.
    2. Chiu-Hsieh Hsu & Jeremy Taylor & Susan Murray, 2004. "Survival Analysis USing Auxiliary Variables Via Nonparametric Multiple Imputation," The University of Michigan Department of Biostatistics Working Paper Series 1026, Berkeley Electronic Press.
    3. Chiu-Hsieh Hsu & Jeremy Taylor & Susan Murray, 2004. "Multiple Imputation For Interval Censored Data With Auxiliary Variables," The University of Michigan Department of Biostatistics Working Paper Series 1025, Berkeley Electronic Press.

    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. 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. Kwon, Tae Yeon & Park, Yousung, 2015. "A new multiple imputation method for bounded missing values," Statistics & Probability Letters, Elsevier, vol. 107(C), pages 204-209.
    3. repec:jss:jstsof:45:i02 is not listed on IDEAS
    4. Wenqing Jiang & Jiangjie Zhou & Baosheng Liang, 2023. "An Improved Dunnett’s Procedure for Comparing Multiple Treatments with a Control in the Presence of Missing Observations," Mathematics, MDPI, vol. 11(14), pages 1-16, July.
    5. Encarnita Mariotti-Ferrandiz & Hang-Phuong Pham & Sophie Dulauroy & Olivier Gorgette & David Klatzmann & Pierre-André Cazenave & Sylviane Pied & Adrien Six, 2016. "A TCRβ Repertoire Signature Can Predict Experimental Cerebral Malaria," PLOS ONE, Public Library of Science, vol. 11(2), pages 1-17, February.
    6. Chaton, Corinne & Gouraud, Alexandre, 2020. "Simulation of fuel poverty in France," Energy Policy, Elsevier, vol. 140(C).
    7. Lana Salih Joelsson & Evangelia Elenis & Kjell Wanggren & Anna Berglund & Anastasia N Iliadou & Carolyn E Cesta & Sunni L Mumford & Richard White & Tanja Tydén & Alkistis Skalkidou, 2019. "Investigating the effect of lifestyle risk factors upon number of aspirated and mature oocytes in in vitro fertilization cycles: Interaction with antral follicle count," PLOS ONE, Public Library of Science, vol. 14(8), pages 1-15, August.
    8. Patrick Lloyd‐Smith, 2021. "The economic benefits of recreation in Canada," Canadian Journal of Economics/Revue canadienne d'économique, John Wiley & Sons, vol. 54(4), pages 1684-1715, November.
    9. Patrick M. Joyce & Donald Malec & Roderick J. A. Little & Aaron Gilary & Alfredo Navarro & Mark E. Asiala, 2014. "Statistical Modeling Methodology for the Voting Rights Act Section 203 Language Assistance Determinations," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 109(505), pages 36-47, March.
    10. Gabriele Beissel Durrant, 2009. "Imputation Methods for Handling Item-Nonresponse in the Social Sciences: A Methodological Review," Working Papers id:2007, eSocialSciences.
    11. Shu Yang & Jae Kwang Kim, 2020. "Asymptotic theory and inference of predictive mean matching imputation using a superpopulation model framework," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 47(3), pages 839-861, September.
    12. Maaz Gardezi & J. Gordon Arbuckle, 2019. "Spatially Representing Vulnerability to Extreme Rain Events Using Midwestern Farmers’ Objective and Perceived Attributes of Adaptive Capacity," Risk Analysis, John Wiley & Sons, vol. 39(1), pages 17-34, January.
    13. Polemis, Michael L. & Fafaliou, Irene, 2015. "Electricity regulation and FDIs spillovers in the OECD: A panel data econometric approach," The Journal of Economic Asymmetries, Elsevier, vol. 12(2), pages 110-123.
    14. Moritz Kuhn & Moritz Schularick & Ulrike I. Steins, 2020. "Income and Wealth Inequality in America, 1949–2016," Journal of Political Economy, University of Chicago Press, vol. 128(9), pages 3469-3519.
    15. Michael L. Polemis & Thanasis Stengos, 2017. "Electricity Sector Performance: A Panel Threshold Analysis," The Energy Journal, International Association for Energy Economics, vol. 0(Number 3).
    16. Urko Aguirre-Larracoechea & Cruz E. Borges, 2021. "Imputation for Repeated Bounded Outcome Data: Statistical and Machine-Learning Approaches," Mathematics, MDPI, vol. 9(17), pages 1-27, August.
    17. Leonardo Letelier S & Hector Ormeño C, 2018. "Education and fiscal decentralization. The case of municipal education in Chile," Environment and Planning C, , vol. 36(8), pages 1499-1521, December.
    18. Jeffrey Max & Jill Constantine & Alison Wellington & Kristin Hallgren & Steven Glazerman & Hanley Chiang & Cecilia Speroni, "undated". "Evaluation of the Teacher Incentive Fund: Implementation and Early Impacts of Pay-for-Performance After One Year," Mathematica Policy Research Reports a8016bcc5b4248c2a8e583ee5, Mathematica Policy Research.
    19. Bilge Erten & Pinar Keskin, 2024. "Trade-offs? The Impact of WTO Accession on Intimate Partner Violence in Cambodia," The Review of Economics and Statistics, MIT Press, vol. 106(2), pages 322-333, March.
    20. Alina K. Bartscher & Moritz Kuhn & Moritz Schularick, 2020. "The College Wealth Divide: Education and Inequality in America, 1956-2016," Review, Federal Reserve Bank of St. Louis, vol. 102(1), pages 19-49.
    21. Ahmad R. Alsaber & Jiazhu Pan & Adeeba Al-Hurban, 2021. "Handling Complex Missing Data Using Random Forest Approach for an Air Quality Monitoring Dataset: A Case Study of Kuwait Environmental Data (2012 to 2018)," IJERPH, MDPI, vol. 18(3), pages 1-25, February.

    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:stapro:v:58:y:2002:i:3:p:221-232. 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/wps/find/journaldescription.cws_home/622892/description#description .

    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.