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 *

141 related articles for article (PubMed ID: 28334230)

  • 1. Guided Bayesian imputation to adjust for confounding when combining heterogeneous data sources in comparative effectiveness research.
    Antonelli J; Zigler C; Dominici F
    Biostatistics; 2017 Jul; 18(3):553-568. PubMed ID: 28334230
    [TBL] [Abstract][Full Text] [Related]  

  • 2. Accounting for uncertainty in confounder and effect modifier selection when estimating average causal effects in generalized linear models.
    Wang C; Dominici F; Parmigiani G; Zigler CM
    Biometrics; 2015 Sep; 71(3):654-65. PubMed ID: 25899155
    [TBL] [Abstract][Full Text] [Related]  

  • 3. An Approach to Addressing Multiple Imputation Model Uncertainty Using Bayesian Model Averaging.
    Kaplan D; Yavuz S
    Multivariate Behav Res; 2020; 55(4):553-567. PubMed ID: 31538505
    [TBL] [Abstract][Full Text] [Related]  

  • 4. Uncertainty in Propensity Score Estimation: Bayesian Methods for Variable Selection and Model Averaged Causal Effects.
    Zigler CM; Dominici F
    J Am Stat Assoc; 2014 Jan; 109(505):95-107. PubMed ID: 24696528
    [TBL] [Abstract][Full Text] [Related]  

  • 5. Sequential BART for imputation of missing covariates.
    Xu D; Daniels MJ; Winterstein AG
    Biostatistics; 2016 Jul; 17(3):589-602. PubMed ID: 26980459
    [TBL] [Abstract][Full Text] [Related]  

  • 6. Evaluating the impact of unmeasured confounding with internal validation data: an example cost evaluation in type 2 diabetes.
    Faries D; Peng X; Pawaskar M; Price K; Stamey JD; Seaman JW
    Value Health; 2013; 16(2):259-66. PubMed ID: 23538177
    [TBL] [Abstract][Full Text] [Related]  

  • 7. Bayesian nonparametric adjustment of confounding.
    Kim C; Tec M; Zigler C
    Biometrics; 2023 Dec; 79(4):3252-3265. PubMed ID: 36718599
    [TBL] [Abstract][Full Text] [Related]  

  • 8. Nonlinear multiple imputation for continuous covariate within semiparametric Cox model: application to HIV data in Senegal.
    Mbougua JB; Laurent C; Ndoye I; Delaporte E; Gwet H; Molinari N
    Stat Med; 2013 Nov; 32(26):4651-65. PubMed ID: 23712767
    [TBL] [Abstract][Full Text] [Related]  

  • 9. Model-averaged confounder adjustment for estimating multivariate exposure effects with linear regression.
    Wilson A; Zigler CM; Patel CJ; Dominici F
    Biometrics; 2018 Sep; 74(3):1034-1044. PubMed ID: 29569228
    [TBL] [Abstract][Full Text] [Related]  

  • 10. Bayesian causal inference for observational studies with missingness in covariates and outcomes.
    Zang H; Kim HJ; Huang B; Szczesniak R
    Biometrics; 2023 Dec; 79(4):3624-3636. PubMed ID: 37553770
    [TBL] [Abstract][Full Text] [Related]  

  • 11. Part 2. Development of Enhanced Statistical Methods for Assessing Health Effects Associated with an Unknown Number of Major Sources of Multiple Air Pollutants.
    Park ES; Symanski E; Han D; Spiegelman C
    Res Rep Health Eff Inst; 2015 Jun; (183 Pt 1-2):51-113. PubMed ID: 26333239
    [TBL] [Abstract][Full Text] [Related]  

  • 12. "A Bayesian sensitivity analysis to evaluate the impact of unmeasured confounding with external data: a real world comparative effectiveness study in osteoporosis".
    Zhang X; Faries DE; Boytsov N; Stamey JD; Seaman JW
    Pharmacoepidemiol Drug Saf; 2016 Sep; 25(9):982-92. PubMed ID: 27396534
    [TBL] [Abstract][Full Text] [Related]  

  • 13. Data-driven confounder selection via Markov and Bayesian networks.
    Häggström J
    Biometrics; 2018 Jun; 74(2):389-398. PubMed ID: 29096036
    [TBL] [Abstract][Full Text] [Related]  

  • 14. Bayesian nonparametric generative models for causal inference with missing at random covariates.
    Roy J; Lum KJ; Zeldow B; Dworkin JD; Re VL; Daniels MJ
    Biometrics; 2018 Dec; 74(4):1193-1202. PubMed ID: 29579341
    [TBL] [Abstract][Full Text] [Related]  

  • 15. A comparison of sensitivity-specificity imputation, direct imputation and fully Bayesian analysis to adjust for exposure misclassification when validation data are unavailable.
    Corbin M; Haslett S; Pearce N; Maule M; Greenland S
    Int J Epidemiol; 2017 Jun; 46(3):1063-1072. PubMed ID: 28338966
    [TBL] [Abstract][Full Text] [Related]  

  • 16. A hybrid imputation approach for microarray missing value estimation.
    Li H; Zhao C; Shao F; Li GZ; Wang X
    BMC Genomics; 2015; 16 Suppl 9(Suppl 9):S1. PubMed ID: 26330180
    [TBL] [Abstract][Full Text] [Related]  

  • 17. Dealing with missing covariates in epidemiologic studies: a comparison between multiple imputation and a full Bayesian approach.
    Erler NS; Rizopoulos D; Rosmalen Jv; Jaddoe VW; Franco OH; Lesaffre EM
    Stat Med; 2016 Jul; 35(17):2955-74. PubMed ID: 27042954
    [TBL] [Abstract][Full Text] [Related]  

  • 18. Bayesian effect estimation accounting for adjustment uncertainty.
    Wang C; Parmigiani G; Dominici F
    Biometrics; 2012 Sep; 68(3):661-71. PubMed ID: 22364439
    [TBL] [Abstract][Full Text] [Related]  

  • 19. Combining information from two data sources with misreporting and incompleteness to assess hospice-use among cancer patients: a multiple imputation approach.
    He Y; Landrum MB; Zaslavsky AM
    Stat Med; 2014 Sep; 33(21):3710-24. PubMed ID: 24804628
    [TBL] [Abstract][Full Text] [Related]  

  • 20. [How to adjust confounders in studies on observational comparative effectiveness: (3) approaches on sensitivity analysis for confounder adjustment].
    Huang LL; Zhao Y; Wei YY; Chen F
    Zhonghua Liu Xing Bing Xue Za Zhi; 2019 Dec; 40(12):1645-1649. PubMed ID: 32062931
    [TBL] [Abstract][Full Text] [Related]  

    [Next]    [New Search]
    of 8.