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 *

1221 related articles for article (PubMed ID: 28877666)

  • 21. Rounding strategies for multiply imputed binary data.
    Demirtas H
    Biom J; 2009 Aug; 51(4):677-88. PubMed ID: 19650057
    [TBL] [Abstract][Full Text] [Related]  

  • 22. A Comparison of Multilevel Imputation Schemes for Random Coefficient Models: Fully Conditional Specification and Joint Model Imputation with Random Covariance Matrices.
    Enders CK; Hayes T; Du H
    Multivariate Behav Res; 2018; 53(5):695-713. PubMed ID: 30693802
    [TBL] [Abstract][Full Text] [Related]  

  • 23. Should multiple imputation be the method of choice for handling missing data in randomized trials?
    Sullivan TR; White IR; Salter AB; Ryan P; Lee KJ
    Stat Methods Med Res; 2018 Sep; 27(9):2610-2626. PubMed ID: 28034175
    [TBL] [Abstract][Full Text] [Related]  

  • 24. Multiple imputation in the presence of non-normal data.
    Lee KJ; Carlin JB
    Stat Med; 2017 Feb; 36(4):606-617. PubMed ID: 27862164
    [TBL] [Abstract][Full Text] [Related]  

  • 25. Treatment of nonignorable missing data when modeling unobserved heterogeneity with finite mixture models.
    Lehmann T; Schlattmann P
    Biom J; 2017 Jan; 59(1):159-171. PubMed ID: 27804147
    [TBL] [Abstract][Full Text] [Related]  

  • 26. Model development including interactions with multiple imputed data.
    Hendry GM; Naidoo RN; Zewotir T; North D; Mentz G
    BMC Med Res Methodol; 2014 Dec; 14():136. PubMed ID: 25524532
    [TBL] [Abstract][Full Text] [Related]  

  • 27. Comparison of methods for imputing limited-range variables: a simulation study.
    Rodwell L; Lee KJ; Romaniuk H; Carlin JB
    BMC Med Res Methodol; 2014 Apr; 14():57. PubMed ID: 24766825
    [TBL] [Abstract][Full Text] [Related]  

  • 28. Evaluation of approaches for multiple imputation of three-level data.
    Wijesuriya R; Moreno-Betancur M; Carlin JB; Lee KJ
    BMC Med Res Methodol; 2020 Aug; 20(1):207. PubMed ID: 32787781
    [TBL] [Abstract][Full Text] [Related]  

  • 29. Propensity score analysis with partially observed covariates: How should multiple imputation be used?
    Leyrat C; Seaman SR; White IR; Douglas I; Smeeth L; Kim J; Resche-Rigon M; Carpenter JR; Williamson EJ
    Stat Methods Med Res; 2019 Jan; 28(1):3-19. PubMed ID: 28573919
    [TBL] [Abstract][Full Text] [Related]  

  • 30. Recovery of information from multiple imputation: a simulation study.
    Lee KJ; Carlin JB
    Emerg Themes Epidemiol; 2012 Jun; 9(1):3. PubMed ID: 22695083
    [TBL] [Abstract][Full Text] [Related]  

  • 31. Multiple imputation with sequential penalized regression.
    Zahid FM; Heumann C
    Stat Methods Med Res; 2019 May; 28(5):1311-1327. PubMed ID: 29451087
    [TBL] [Abstract][Full Text] [Related]  

  • 32. 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]  

  • 33. Multiple imputation in Cox regression when there are time-varying effects of covariates.
    Keogh RH; Morris TP
    Stat Med; 2018 Nov; 37(25):3661-3678. PubMed ID: 30014575
    [TBL] [Abstract][Full Text] [Related]  

  • 34. Missing data in the American College of Surgeons National Surgical Quality Improvement Program are not missing at random: implications and potential impact on quality assessments.
    Hamilton BH; Ko CY; Richards K; Hall BL
    J Am Coll Surg; 2010 Feb; 210(2):125-139.e2. PubMed ID: 20113932
    [TBL] [Abstract][Full Text] [Related]  

  • 35. Multiple imputation of covariates by fully conditional specification: Accommodating the substantive model.
    Bartlett JW; Seaman SR; White IR; Carpenter JR;
    Stat Methods Med Res; 2015 Aug; 24(4):462-87. PubMed ID: 24525487
    [TBL] [Abstract][Full Text] [Related]  

  • 36. Multiple imputation methods for handling incomplete longitudinal and clustered data where the target analysis is a linear mixed effects model.
    Huque MH; Moreno-Betancur M; Quartagno M; Simpson JA; Carlin JB; Lee KJ
    Biom J; 2020 Mar; 62(2):444-466. PubMed ID: 31919921
    [TBL] [Abstract][Full Text] [Related]  

  • 37. Multiple Imputation for Incomplete Data in Environmental Epidemiology Research.
    Allotey PA; Harel O
    Curr Environ Health Rep; 2019 Jun; 6(2):62-71. PubMed ID: 31090043
    [TBL] [Abstract][Full Text] [Related]  

  • 38. The rise of multiple imputation: a review of the reporting and implementation of the method in medical research.
    Hayati Rezvan P; Lee KJ; Simpson JA
    BMC Med Res Methodol; 2015 Apr; 15():30. PubMed ID: 25880850
    [TBL] [Abstract][Full Text] [Related]  

  • 39. Estimating range of influence in case of missing spatial data: a simulation study on binary data.
    Bihrmann K; Ersbøll AK
    Int J Health Geogr; 2015 Jan; 14():1. PubMed ID: 25563056
    [TBL] [Abstract][Full Text] [Related]  

  • 40. A nonparametric multiple imputation approach for missing categorical data.
    Zhou M; He Y; Yu M; Hsu CH
    BMC Med Res Methodol; 2017 Jun; 17(1):87. PubMed ID: 28587662
    [TBL] [Abstract][Full Text] [Related]  

    [Previous]   [Next]    [New Search]
    of 62.