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There are 188802 results for: content related to: A comparison of multiple imputation and fully augmented weighted estimators for Cox regression with missing covariates

  1. You have free access to this content
    Bibliography

    Multiple Imputation and its Application

    James R. Carpenter, Michael G. Kenward, Pages: 316–326, 2012

    Published Online : 18 DEC 2012, DOI: 10.1002/9781119942283.biblio

  2. Fitting additive hazards models for case-cohort studies: a multiple imputation approach

    Statistics in Medicine

    Jinhyouk Jung, Ofer Harel and Sangwook Kang

    Article first published online : 20 JUL 2015, DOI: 10.1002/sim.6588

  3. You have full text access to this OnlineOpen article
    Combining Multiple Imputation and Inverse-Probability Weighting

    Biometrics

    Volume 68, Issue 1, March 2012, Pages: 129–137, Shaun R. Seaman, Ian R. White, Andrew J. Copas and Leah Li

    Article first published online : 3 NOV 2011, DOI: 10.1111/j.1541-0420.2011.01666.x

  4. Multiple imputation by chained equations: what is it and how does it work?

    International Journal of Methods in Psychiatric Research

    Volume 20, Issue 1, March 2011, Pages: 40–49, Melissa J. Azur, Elizabeth A. Stuart, Constantine Frangakis and Philip J. Leaf

    Article first published online : 24 FEB 2011, DOI: 10.1002/mpr.329

  5. Nonlinear multiple imputation for continuous covariate within semiparametric Cox model: application to HIV data in Senegal

    Statistics in Medicine

    Volume 32, Issue 26, 20 November 2013, Pages: 4651–4665, Jules Brice Tchatchueng Mbougua, Christian Laurent, Ibra Ndoye, Eric Delaporte, Henri Gwet and Nicolas Molinari

    Article first published online : 28 MAY 2013, DOI: 10.1002/sim.5854

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    Bibliography

    Clinical Trials with Missing Data: A Guide for Practitioners

    Michael O'Kelly, Bohdana Ratitch, Pages: 409–421, 2014

    Published Online : 21 FEB 2014, DOI: 10.1002/9781118762516.biblio

  7. Multiple imputation of missing dual-energy X-ray absorptiometry data in the National Health and Nutrition Examination Survey

    Statistics in Medicine

    Volume 30, Issue 3, 10 February 2011, Pages: 260–276, Nathaniel Schenker, Lori G. Borrud, Vicki L. Burt, Lester R. Curtin, Katherine M. Flegal, Jeffery Hughes, Clifford L. Johnson, Anne C. Looker and Lisa Mirel

    Article first published online : 30 NOV 2010, DOI: 10.1002/sim.4080

  8. A Review of Hot Deck Imputation for Survey Non-response

    International Statistical Review

    Volume 78, Issue 1, April 2010, Pages: 40–64, Rebecca R. Andridge and Roderick J. A. Little

    Article first published online : 10 MAR 2010, DOI: 10.1111/j.1751-5823.2010.00103.x

  9. Dealing with missing covariates in epidemiologic studies: a comparison between multiple imputation and a full Bayesian approach

    Statistics in Medicine

    Nicole S. Erler, Dimitris Rizopoulos, Joost van Rosmalen, Vincent W. V. Jaddoe, Oscar H. Franco and Emmanuel M. E. H. Lesaffre

    Article first published online : 4 APR 2016, DOI: 10.1002/sim.6944

  10. A functional multiple imputation approach to incomplete longitudinal data

    Statistics in Medicine

    Volume 30, Issue 10, 10 May 2011, Pages: 1137–1156, Yulei He, Recai Yucel and Trivellore E. Raghunathan

    Article first published online : 22 FEB 2011, DOI: 10.1002/sim.4201

  11. Multiple imputation of incomplete zero-inflated count data

    Statistica Neerlandica

    Volume 67, Issue 3, August 2013, Pages: 311–336, Kristian Kleinke and Jost Reinecke

    Article first published online : 17 MAY 2013, DOI: 10.1111/stan.12009

  12. Missing Data

    Standard Article

    Developmental Psychopathology

    Todd D. Little, Kyle M. Lang, Wei Wu and Mijke Rhemtulla

    Published Online : 10 FEB 2016, DOI: 10.1002/9781119125556.devpsy117

  13. Imputation

    Wiley Interdisciplinary Reviews: Computational Statistics

    Volume 5, Issue 1, January/February 2013, Pages: 20–29, Susanne Rässler, Donald B. Rubin and Elizabeth R. Zell

    Article first published online : 26 DEC 2012, DOI: 10.1002/wics.1240

  14. Working With Missing Values

    Journal of Marriage and Family

    Volume 67, Issue 4, November 2005, Pages: 1012–1028, Alan C. Acock

    Article first published online : 20 SEP 2005, DOI: 10.1111/j.1741-3737.2005.00191.x

  15. A comparison of multiple-imputation methods for handling missing data in repeated measurements observational studies

    Journal of the Royal Statistical Society: Series A (Statistics in Society)

    Oya Kalaycioglu, Andrew Copas, Michael King and Rumana Z. Omar

    Article first published online : 15 OCT 2015, DOI: 10.1111/rssa.12140

  16. You have full text access to this OnlineOpen article
    Multiple imputation and analysis for high-dimensional incomplete proteomics data

    Statistics in Medicine

    Volume 35, Issue 8, 15 April 2016, Pages: 1315–1326, Xiaoyan Yin, Daniel Levy, Christine Willinger, Aram Adourian and Martin G. Larson

    Article first published online : 12 NOV 2015, DOI: 10.1002/sim.6800

  17. Missing Data and Imputation Methods

    Modern Analysis of Customer Surveys: With Applications Using R

    Alessandra Mattei, Fabrizia Mealli, Donald B. Rubin, Pages: 129–154, 2011

    Published Online : 9 NOV 2011, DOI: 10.1002/9781119961154.ch8

  18. Multiple imputation for completion of a national clinical audit dataset

    Statistics in Medicine

    Volume 30, Issue 22, 30 September 2011, Pages: 2736–2753, Brian A. Cattle, Paul D. Baxter, Darren C. Greenwood, Christopher P. Gale and Robert M. West

    Article first published online : 22 JUL 2011, DOI: 10.1002/sim.4314

  19. Imputation of systematically missing predictors in an individual participant data meta-analysis: a generalized approach using MICE

    Statistics in Medicine

    Volume 34, Issue 11, 20 May 2015, Pages: 1841–1863, Shahab Jolani, Thomas P. A. Debray, Hendrik Koffijberg, Stef van Buuren and Karel G. M. Moons

    Article first published online : 9 FEB 2015, DOI: 10.1002/sim.6451

  20. On the bias of the multiple-imputation variance estimator in survey sampling

    Journal of the Royal Statistical Society: Series B (Statistical Methodology)

    Volume 68, Issue 3, June 2006, Pages: 509–521, Jae Kwang Kim, J. Michael Brick, Wayne A. Fuller and Graham Kalton

    Article first published online : 4 APR 2006, DOI: 10.1111/j.1467-9868.2006.00546.x