BIOMARKERS

Molecular Biopsy of Human Tumors

- a resource for Precision Medicine *

332 related articles for article (PubMed ID: 23913915)

  • 1. 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; 33(8):1051-63. PubMed ID: 23913915
    [TBL] [Abstract][Full Text] [Related]  

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

  • 3. Developing appropriate methods for cost-effectiveness analysis of cluster randomized trials.
    Gomes M; Ng ES; Grieve R; Nixon R; Carpenter J; Thompson SG
    Med Decis Making; 2012; 32(2):350-61. PubMed ID: 22016450
    [TBL] [Abstract][Full Text] [Related]  

  • 4. Is using multiple imputation better than complete case analysis for estimating a prevalence (risk) difference in randomized controlled trials when binary outcome observations are missing?
    Mukaka M; White SA; Terlouw DJ; Mwapasa V; Kalilani-Phiri L; Faragher EB
    Trials; 2016 Jul; 17():341. PubMed ID: 27450066
    [TBL] [Abstract][Full Text] [Related]  

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

  • 6. Comparison of techniques for handling missing covariate data within prognostic modelling studies: a simulation study.
    Marshall A; Altman DG; Royston P; Holder RL
    BMC Med Res Methodol; 2010 Jan; 10():7. PubMed ID: 20085642
    [TBL] [Abstract][Full Text] [Related]  

  • 7. Approaches for missing covariate data in logistic regression with MNAR sensitivity analyses.
    Ward RC; Axon RN; Gebregziabher M
    Biom J; 2020 Jul; 62(4):1025-1037. PubMed ID: 31957905
    [TBL] [Abstract][Full Text] [Related]  

  • 8. Multiple imputation strategies for zero-inflated cost data in economic evaluations: which method works best?
    MacNeil Vroomen J; Eekhout I; Dijkgraaf MG; van Hout H; de Rooij SE; Heymans MW; Bosmans JE
    Eur J Health Econ; 2016 Nov; 17(8):939-950. PubMed ID: 26497027
    [TBL] [Abstract][Full Text] [Related]  

  • 9. How to deal with missing longitudinal data in cost of illness analysis in Alzheimer's disease-suggestions from the GERAS observational study.
    Belger M; Haro JM; Reed C; Happich M; Kahle-Wrobleski K; Argimon JM; Bruno G; Dodel R; Jones RW; Vellas B; Wimo A
    BMC Med Res Methodol; 2016 Jul; 16():83. PubMed ID: 27430559
    [TBL] [Abstract][Full Text] [Related]  

  • 10. Is the whole larger than the sum of its parts? Impact of missing data imputation in economic evaluation conducted alongside randomized controlled trials.
    Michalowsky B; Hoffmann W; Kennedy K; Xie F
    Eur J Health Econ; 2020 Jul; 21(5):717-728. PubMed ID: 32108274
    [TBL] [Abstract][Full Text] [Related]  

  • 11. Comparison of methods for handling missing data on immunohistochemical markers in survival analysis of breast cancer.
    Ali AM; Dawson SJ; Blows FM; Provenzano E; Ellis IO; Baglietto L; Huntsman D; Caldas C; Pharoah PD
    Br J Cancer; 2011 Feb; 104(4):693-9. PubMed ID: 21266980
    [TBL] [Abstract][Full Text] [Related]  

  • 12. 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; 29(5):1338-1353. PubMed ID: 31293199
    [TBL] [Abstract][Full Text] [Related]  

  • 13. Missing continuous outcomes under covariate dependent missingness in cluster randomised trials.
    Hossain A; Diaz-Ordaz K; Bartlett JW
    Stat Methods Med Res; 2017 Jun; 26(3):1543-1562. PubMed ID: 27177885
    [TBL] [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; 13():9. PubMed ID: 23343209
    [TBL] [Abstract][Full Text] [Related]  

  • 15. Multiple imputation by predictive mean matching in cluster-randomized trials.
    Bailey BE; Andridge R; Shoben AB
    BMC Med Res Methodol; 2020 Mar; 20(1):72. PubMed ID: 32228491
    [TBL] [Abstract][Full Text] [Related]  

  • 16. A Scoping Review of Item-Level Missing Data in Within-Trial Cost-Effectiveness Analysis.
    Ling X; Gabrio A; Mason A; Baio G
    Value Health; 2022 Sep; 25(9):1654-1662. PubMed ID: 35341690
    [TBL] [Abstract][Full Text] [Related]  

  • 17. Imputation of missing covariate in randomized controlled trials with a continuous outcome: Scoping review and new results.
    Kayembe MT; Jolani S; Tan FES; van Breukelen GJP
    Pharm Stat; 2020 Nov; 19(6):840-860. PubMed ID: 32510791
    [TBL] [Abstract][Full Text] [Related]  

  • 18. Bayesian hierarchical models for cost-effectiveness analyses that use data from cluster randomized trials.
    Grieve R; Nixon R; Thompson SG
    Med Decis Making; 2010; 30(2):163-75. PubMed ID: 19675321
    [TBL] [Abstract][Full Text] [Related]  

  • 19. A multiple imputation approach for MNAR mechanisms compatible with Heckman's model.
    Galimard JE; Chevret S; Protopopescu C; Resche-Rigon M
    Stat Med; 2016 Jul; 35(17):2907-20. PubMed ID: 26893215
    [TBL] [Abstract][Full Text] [Related]  

  • 20. Evaluation of a weighting approach for performing sensitivity analysis after multiple imputation.
    Rezvan PH; White IR; Lee KJ; Carlin JB; Simpson JA
    BMC Med Res Methodol; 2015 Oct; 15():83. PubMed ID: 26464305
    [TBL] [Abstract][Full Text] [Related]  

    [Next]    [New Search]
    of 17.