These tools will no longer be maintained as of December 31, 2024. Archived website can be found here. PubMed4Hh GitHub repository can be found here. Contact NLM Customer Service if you have questions.


Pubmed for Handhelds

PUBMED FOR HANDHELDS

Journal Abstract Search

283 related items for PubMed ID: 26990655

  • 1. Multiple imputation methods for bivariate outcomes in cluster randomised trials.
    DiazOrdaz K, Kenward MG, Gomes M, Grieve R.
    Stat Med; 2016 Sep 10; 35(20):3482-96. PubMed ID: 26990655
    [Abstract] [Full Text] [Related]

  • 2. Missing continuous outcomes under covariate dependent missingness in cluster randomised trials.
    Hossain A, Diaz-Ordaz K, Bartlett JW.
    Stat Methods Med Res; 2017 Jun 10; 26(3):1543-1562. PubMed ID: 27177885
    [Abstract] [Full Text] [Related]

  • 3. Multiple imputation methods for handling missing data in cost-effectiveness analyses that use data from hierarchical studies: an application to cluster randomized trials.
    Gomes M, Díaz-Ordaz K, Grieve R, Kenward MG.
    Med Decis Making; 2013 Nov 10; 33(8):1051-63. PubMed ID: 23913915
    [Abstract] [Full Text] [Related]

  • 4. Imputation strategies when a continuous outcome is to be dichotomized for responder analysis: a simulation study.
    Floden L, Bell ML.
    BMC Med Res Methodol; 2019 Jul 23; 19(1):161. PubMed ID: 31345166
    [Abstract] [Full Text] [Related]

  • 5. Missing binary outcomes under covariate-dependent missingness in cluster randomised trials.
    Hossain A, DiazOrdaz K, Bartlett JW.
    Stat Med; 2017 Aug 30; 36(19):3092-3109. PubMed ID: 28557022
    [Abstract] [Full Text] [Related]

  • 6. Properties and pitfalls of weighting as an alternative to multilevel multiple imputation in cluster randomized trials with missing binary outcomes under covariate-dependent missingness.
    Turner EL, Yao L, Li F, Prague M.
    Stat Methods Med Res; 2020 May 30; 29(5):1338-1353. PubMed ID: 31293199
    [Abstract] [Full Text] [Related]

  • 7. Assessing treatment effect heterogeneity in the presence of missing effect modifier data in cluster-randomized trials.
    Blette BS, Halpern SD, Li F, Harhay MO.
    Stat Methods Med Res; 2024 May 30; 33(5):909-927. PubMed ID: 38567439
    [Abstract] [Full Text] [Related]

  • 8. Are missing data adequately handled in cluster randomised trials? A systematic review and guidelines.
    Díaz-Ordaz K, Kenward MG, Cohen A, Coleman CL, Eldridge S.
    Clin Trials; 2014 Oct 30; 11(5):590-600. PubMed ID: 24902924
    [Abstract] [Full Text] [Related]

  • 9. Imputation strategies for missing binary outcomes in cluster randomized trials.
    Ma J, Akhtar-Danesh N, Dolovich L, Thabane L, CHAT investigators.
    BMC Med Res Methodol; 2011 Feb 16; 11():18. PubMed ID: 21324148
    [Abstract] [Full Text] [Related]

  • 10. Appropriate statistical methods for analysing partially nested randomised controlled trials with continuous outcomes: a simulation study.
    Candlish J, Teare MD, Dimairo M, Flight L, Mandefield L, Walters SJ.
    BMC Med Res Methodol; 2018 Oct 11; 18(1):105. PubMed ID: 30314463
    [Abstract] [Full Text] [Related]

  • 11.
    ; . PubMed ID:
    [No Abstract] [Full Text] [Related]

  • 12.
    ; . PubMed ID:
    [No Abstract] [Full Text] [Related]

  • 13.
    ; . PubMed ID:
    [No Abstract] [Full Text] [Related]

  • 14. Comparison of population-averaged and cluster-specific models for the analysis of cluster randomized trials with missing binary outcomes: a simulation study.
    Ma J, Raina P, Beyene J, Thabane L.
    BMC Med Res Methodol; 2013 Jan 23; 13():9. PubMed ID: 23343209
    [Abstract] [Full Text] [Related]

  • 15.
    ; . PubMed ID:
    [No Abstract] [Full Text] [Related]

  • 16.
    ; . PubMed ID:
    [No Abstract] [Full Text] [Related]

  • 17. Evaluation of multiple imputation approaches for handling missing covariate information in a case-cohort study with a binary outcome.
    Middleton M, Nguyen C, Moreno-Betancur M, Carlin JB, Lee KJ.
    BMC Med Res Methodol; 2022 Apr 03; 22(1):87. PubMed ID: 35369860
    [Abstract] [Full Text] [Related]

  • 18. Imputation strategies for missing continuous outcomes in cluster randomized trials.
    Taljaard M, Donner A, Klar N.
    Biom J; 2008 Jun 03; 50(3):329-45. PubMed ID: 18537126
    [Abstract] [Full Text] [Related]

  • 19. When and how should multiple imputation be used for handling missing data in randomised clinical trials - a practical guide with flowcharts.
    Jakobsen JC, Gluud C, Wetterslev J, Winkel P.
    BMC Med Res Methodol; 2017 Dec 06; 17(1):162. PubMed ID: 29207961
    [Abstract] [Full Text] [Related]

  • 20.
    ; . PubMed ID:
    [No Abstract] [Full Text] [Related]

    Page: [Next] [New Search]
    of 15.