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.


BIOMARKERS

Molecular Biopsy of Human Tumors

- a resource for Precision Medicine *

277 related articles for article (PubMed ID: 28579378)

  • 1. A systematic survey of the methods literature on the reporting quality and optimal methods of handling participants with missing outcome data for continuous outcomes in randomized controlled trials.
    Zhang Y; Alyass A; Vanniyasingam T; Sadeghirad B; Flórez ID; Pichika SC; Kennedy SA; Abdulkarimova U; Zhang Y; Iljon T; Morgano GP; Colunga Lozano LE; Aloweni FAB; Lopes LC; Yepes-Nuñez JJ; Fei Y; Wang L; Kahale LA; Meyre D; Akl EA; Thabane L; Guyatt GH
    J Clin Epidemiol; 2017 Aug; 88():67-80. PubMed ID: 28579378
    [TBL] [Abstract][Full Text] [Related]  

  • 2. A systematic survey on reporting and methods for handling missing participant data for continuous outcomes in randomized controlled trials.
    Zhang Y; Flórez ID; Colunga Lozano LE; Aloweni FAB; Kennedy SA; Li A; Craigie S; Zhang S; Agarwal A; Lopes LC; Devji T; Wiercioch W; Riva JJ; Wang M; Jin X; Fei Y; Alexander P; Morgano GP; Zhang Y; Carrasco-Labra A; Kahale LA; Akl EA; Schünemann HJ; Thabane L; Guyatt GH
    J Clin Epidemiol; 2017 Aug; 88():57-66. PubMed ID: 28583378
    [TBL] [Abstract][Full Text] [Related]  

  • 3. Reporting missing participant data in randomised trials: systematic survey of the methodological literature and a proposed guide.
    Akl EA; Shawwa K; Kahale LA; Agoritsas T; Brignardello-Petersen R; Busse JW; Carrasco-Labra A; Ebrahim S; Johnston BC; Neumann I; Sola I; Sun X; Vandvik P; Zhang Y; Alonso-Coello P; Guyatt GH
    BMJ Open; 2015 Dec; 5(12):e008431. PubMed ID: 26719310
    [TBL] [Abstract][Full Text] [Related]  

  • 4. Handling trial participants with missing outcome data when conducting a meta-analysis: a systematic survey of proposed approaches.
    Akl EA; Kahale LA; Agoritsas T; Brignardello-Petersen R; Busse JW; Carrasco-Labra A; Ebrahim S; Johnston BC; Neumann I; Sola I; Sun X; Vandvik P; Zhang Y; Alonso-Coello P; Guyatt G
    Syst Rev; 2015 Jul; 4():98. PubMed ID: 26202162
    [TBL] [Abstract][Full Text] [Related]  

  • 5. MMRM versus MI in dealing with missing data--a comparison based on 25 NDA data sets.
    Siddiqui O
    J Biopharm Stat; 2011 May; 21(3):423-36. PubMed ID: 21442517
    [TBL] [Abstract][Full Text] [Related]  

  • 6. Missing data in randomized controlled trials of rheumatoid arthritis with radiographic outcomes: a simulation study.
    Baron G; Ravaud P; Samson A; Giraudeau B
    Arthritis Rheum; 2008 Jan; 59(1):25-31. PubMed ID: 18163406
    [TBL] [Abstract][Full Text] [Related]  

  • 7. Estimating the effect of multiple imputation on incomplete longitudinal data with application to a randomized clinical study.
    Fong DY; Rai SN; Lam KS
    J Biopharm Stat; 2013; 23(5):1004-22. PubMed ID: 23957512
    [TBL] [Abstract][Full Text] [Related]  

  • 8. Consequences of handling missing data for treatment response in osteoarthritis: a simulation study.
    Olsen IC; Kvien TK; Uhlig T
    Osteoarthritis Cartilage; 2012 Aug; 20(8):822-8. PubMed ID: 22441031
    [TBL] [Abstract][Full Text] [Related]  

  • 9. Comparisons of methods for analysis of repeated binary responses with missing data.
    Frank Liu G; Zhan X
    J Biopharm Stat; 2011 May; 21(3):371-92. PubMed ID: 21442514
    [TBL] [Abstract][Full Text] [Related]  

  • 10. Accounting for dropout bias using mixed-effects models.
    Mallinckrodt CH; Clark WS; David SR
    J Biopharm Stat; 2001; 11(1-2):9-21. PubMed ID: 11459446
    [TBL] [Abstract][Full Text] [Related]  

  • 11. A systematic review of randomised controlled trials in rheumatoid arthritis: the reporting and handling of missing data in composite outcomes.
    Ibrahim F; Tom BD; Scott DL; Prevost AT
    Trials; 2016 Jun; 17(1):272. PubMed ID: 27255212
    [TBL] [Abstract][Full Text] [Related]  

  • 12. The impact of loss to follow-up on hypothesis tests of the treatment effect for several statistical methods in substance abuse clinical trials.
    Hedden SL; Woolson RF; Carter RE; Palesch Y; Upadhyaya HP; Malcolm RJ
    J Subst Abuse Treat; 2009 Jul; 37(1):54-63. PubMed ID: 19008067
    [TBL] [Abstract][Full Text] [Related]  

  • 13. Comparison of data analysis strategies for intent-to-treat analysis in pre-test-post-test designs with substantial dropout rates.
    Salim A; Mackinnon A; Christensen H; Griffiths K
    Psychiatry Res; 2008 Sep; 160(3):335-45. PubMed ID: 18718673
    [TBL] [Abstract][Full Text] [Related]  

  • 14. Accounting for uncertainty due to 'last observation carried forward' outcome imputation in a meta-analysis model.
    Dimitrakopoulou V; Efthimiou O; Leucht S; Salanti G
    Stat Med; 2015 Feb; 34(5):742-52. PubMed ID: 25492741
    [TBL] [Abstract][Full Text] [Related]  

  • 15. Simulation-based study comparing multiple imputation methods for non-monotone missing ordinal data in longitudinal settings.
    Donneau AF; Mauer M; Lambert P; Molenberghs G; Albert A
    J Biopharm Stat; 2015; 25(3):570-601. PubMed ID: 24905056
    [TBL] [Abstract][Full Text] [Related]  

  • 16. A systematic review finds variable use of the intention-to-treat principle in musculoskeletal randomized controlled trials with missing data.
    Joseph R; Sim J; Ogollah R; Lewis M
    J Clin Epidemiol; 2015 Jan; 68(1):15-24. PubMed ID: 25304501
    [TBL] [Abstract][Full Text] [Related]  

  • 17. Move over LOCF: principled methods for handling missing data in sleep disorder trials.
    Olsen MK; Stechuchak KM; Edinger JD; Ulmer CS; Woolson RF
    Sleep Med; 2012 Feb; 13(2):123-32. PubMed ID: 22172964
    [TBL] [Abstract][Full Text] [Related]  

  • 18. Impact of missing participant data for dichotomous outcomes on pooled effect estimates in systematic reviews: a protocol for a methodological study.
    Akl EA; Kahale LA; Agarwal A; Al-Matari N; Ebrahim S; Alexander PE; Briel M; Brignardello-Petersen R; Busse JW; Diab B; Iorio A; Kwong J; Li L; Lopes LC; Mustafa R; Neumann I; Tikkinen KA; Vandvik PO; Zhang Y; Alonso-Coello P; Guyatt G
    Syst Rev; 2014 Nov; 3():137. PubMed ID: 25423894
    [TBL] [Abstract][Full Text] [Related]  

  • 19. Allowing for uncertainty due to missing and LOCF imputed outcomes in meta-analysis.
    Mavridis D; Salanti G; Furukawa TA; Cipriani A; Chaimani A; White IR
    Stat Med; 2019 Feb; 38(5):720-737. PubMed ID: 30347460
    [TBL] [Abstract][Full Text] [Related]  

  • 20. Handling of Missing Outcome Data in Acute Stroke Trials: Advantages of Multiple Imputation Using Baseline and Postbaseline Variables.
    Young-Saver DF; Gornbein J; Starkman S; Saver JL
    J Stroke Cerebrovasc Dis; 2018 Dec; 27(12):3662-3669. PubMed ID: 30297167
    [TBL] [Abstract][Full Text] [Related]  

    [Next]    [New Search]
    of 14.