BIOMARKERS

Molecular Biopsy of Human Tumors

- a resource for Precision Medicine *

134 related articles for article (PubMed ID: 34340246)

  • 1. Estimating the marginal effect of a continuous exposure on an ordinal outcome using data subject to covariate-driven treatment and visit processes.
    Coulombe J; Moodie EEM; Platt RW
    Stat Med; 2021 Nov; 40(26):5746-5764. PubMed ID: 34340246
    [TBL] [Abstract][Full Text] [Related]  

  • 2. Evaluating Flexible Modeling of Continuous Covariates in Inverse-Weighted Estimators.
    Kyle RP; Moodie EEM; Klein MB; Abrahamowicz M
    Am J Epidemiol; 2019 Jun; 188(6):1181-1191. PubMed ID: 30649165
    [TBL] [Abstract][Full Text] [Related]  

  • 3. Weighted regression analysis to correct for informative monitoring times and confounders in longitudinal studies.
    Coulombe J; Moodie EEM; Platt RW
    Biometrics; 2021 Mar; 77(1):162-174. PubMed ID: 32333384
    [TBL] [Abstract][Full Text] [Related]  

  • 4. Doubly-robust methods for differences in restricted mean lifetimes using pseudo-observations.
    Choi S; Choi T; Lee HY; Han SW; Bandyopadhyay D
    Pharm Stat; 2022 Nov; 21(6):1185-1198. PubMed ID: 35524651
    [TBL] [Abstract][Full Text] [Related]  

  • 5. Instrumental variables and inverse probability weighting for causal inference from longitudinal observational studies.
    Hogan JW; Lancaster T
    Stat Methods Med Res; 2004 Feb; 13(1):17-48. PubMed ID: 14746439
    [TBL] [Abstract][Full Text] [Related]  

  • 6. Causal inference in survival analysis using longitudinal observational data: Sequential trials and marginal structural models.
    Keogh RH; Gran JM; Seaman SR; Davies G; Vansteelandt S
    Stat Med; 2023 Jun; 42(13):2191-2225. PubMed ID: 37086186
    [TBL] [Abstract][Full Text] [Related]  

  • 7. A weighting method for simultaneous adjustment for confounding and joint exposure-outcome misclassifications.
    Penning de Vries BB; van Smeden M; Groenwold RH
    Stat Methods Med Res; 2021 Feb; 30(2):473-487. PubMed ID: 32998668
    [TBL] [Abstract][Full Text] [Related]  

  • 8. Marginal structural models in clinical research: when and how to use them?
    Williamson T; Ravani P
    Nephrol Dial Transplant; 2017 Apr; 32(suppl_2):ii84-ii90. PubMed ID: 28201767
    [TBL] [Abstract][Full Text] [Related]  

  • 9. Data-adaptive longitudinal model selection in causal inference with collaborative targeted minimum loss-based estimation.
    Schnitzer ME; Sango J; Ferreira Guerra S; van der Laan MJ
    Biometrics; 2020 Mar; 76(1):145-157. PubMed ID: 31397506
    [TBL] [Abstract][Full Text] [Related]  

  • 10. Reflection on modern methods: combining weights for confounding and missing data.
    Ross RK; Breskin A; Breger TL; Westreich D
    Int J Epidemiol; 2022 May; 51(2):679-684. PubMed ID: 34536004
    [TBL] [Abstract][Full Text] [Related]  

  • 11. A test for the correct specification of marginal structural models.
    Sall A; Aubé K; Trudel X; Brisson C; Talbot D
    Stat Med; 2019 Jul; 38(17):3168-3183. PubMed ID: 30856294
    [TBL] [Abstract][Full Text] [Related]  

  • 12. Causal models adjusting for time-varying confounding-a systematic review of the literature.
    Clare PJ; Dobbins TA; Mattick RP
    Int J Epidemiol; 2019 Feb; 48(1):254-265. PubMed ID: 30358847
    [TBL] [Abstract][Full Text] [Related]  

  • 13. Correcting for Measurement Error in Time-Varying Covariates in Marginal Structural Models.
    Kyle RP; Moodie EE; Klein MB; Abrahamowicz M
    Am J Epidemiol; 2016 Aug; 184(3):249-58. PubMed ID: 27416840
    [TBL] [Abstract][Full Text] [Related]  

  • 14. Causal inference with longitudinal data subject to irregular assessment times.
    Pullenayegum EM; Birken C; Maguire J;
    Stat Med; 2023 Jun; 42(14):2361-2393. PubMed ID: 37054723
    [TBL] [Abstract][Full Text] [Related]  

  • 15. Joint calibrated estimation of inverse probability of treatment and censoring weights for marginal structural models.
    Yiu S; Su L
    Biometrics; 2022 Mar; 78(1):115-127. PubMed ID: 33247594
    [TBL] [Abstract][Full Text] [Related]  

  • 16. Causal inference with noisy data: Bias analysis and estimation approaches to simultaneously addressing missingness and misclassification in binary outcomes.
    Shu D; Yi GY
    Stat Med; 2020 Feb; 39(4):456-468. PubMed ID: 31802532
    [TBL] [Abstract][Full Text] [Related]  

  • 17. Weighted estimation for confounded binary outcomes subject to misclassification.
    Gravel CA; Platt RW
    Stat Med; 2018 Feb; 37(3):425-436. PubMed ID: 29082530
    [TBL] [Abstract][Full Text] [Related]  

  • 18. Confounding-adjustment methods for the causal difference in medians.
    Shepherd DA; Baer BR; Moreno-Betancur M
    BMC Med Res Methodol; 2023 Dec; 23(1):288. PubMed ID: 38062364
    [TBL] [Abstract][Full Text] [Related]  

  • 19. Time dependent hazard ratio estimation using instrumental variables without conditioning on an omitted covariate.
    MacKenzie TA; Martinez-Camblor P; O'Malley AJ
    BMC Med Res Methodol; 2021 Mar; 21(1):56. PubMed ID: 33743583
    [TBL] [Abstract][Full Text] [Related]  

  • 20. Marginal analysis of longitudinal ordinal data with misclassification in both response and covariates.
    Chen Z; Yi GY; Wu C
    Biom J; 2014 Jan; 56(1):69-85. PubMed ID: 24123126
    [TBL] [Abstract][Full Text] [Related]  

    [Next]    [New Search]
    of 7.