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 *

179 related articles for article (PubMed ID: 32762994)

  • 1. Nonproportional Hazards in Network Meta-Analysis: Efficient Strategies for Model Building and Analysis.
    Wiksten A; Hawkins N; Piepho HP; Gsteiger S
    Value Health; 2020 Jul; 23(7):918-927. PubMed ID: 32762994
    [TBL] [Abstract][Full Text] [Related]  

  • 2. A Comparison of Alternative Network Meta-Analysis Methods in the Presence of Nonproportional Hazards: A Case Study in First-Line Advanced or Metastatic Renal Cell Carcinoma.
    Cope S; Chan K; Campbell H; Chen J; Borrill J; May JR; Malcolm W; Branchoux S; Kupas K; Jansen JP
    Value Health; 2023 Apr; 26(4):465-476. PubMed ID: 36503035
    [TBL] [Abstract][Full Text] [Related]  

  • 3. Theory and practice of Bayesian and frequentist frameworks for network meta-analysis.
    Sadeghirad B; Foroutan F; Zoratti MJ; Busse JW; Brignardello-Petersen R; Guyatt G; Thabane L
    BMJ Evid Based Med; 2023 Jun; 28(3):204-209. PubMed ID: 35760451
    [TBL] [Abstract][Full Text] [Related]  

  • 4. Challenges of modelling approaches for network meta-analysis of time-to-event outcomes in the presence of non-proportional hazards to aid decision making: Application to a melanoma network.
    Freeman SC; Cooper NJ; Sutton AJ; Crowther MJ; Carpenter JR; Hawkins N
    Stat Methods Med Res; 2022 May; 31(5):839-861. PubMed ID: 35044255
    [TBL] [Abstract][Full Text] [Related]  

  • 5. A comparative review of network meta-analysis models in longitudinal randomized controlled trial.
    Tallarita M; De Iorio M; Baio G
    Stat Med; 2019 Jul; 38(16):3053-3072. PubMed ID: 31050822
    [TBL] [Abstract][Full Text] [Related]  

  • 6. Quantitative summaries of treatment effect estimates obtained with network meta-analysis of survival curves to inform decision-making.
    Cope S; Jansen JP
    BMC Med Res Methodol; 2013 Dec; 13():147. PubMed ID: 24289277
    [TBL] [Abstract][Full Text] [Related]  

  • 7. A design-by-treatment interaction model for network meta-analysis and meta-regression with integrated nested Laplace approximations.
    Günhan BK; Friede T; Held L
    Res Synth Methods; 2018 Jun; 9(2):179-194. PubMed ID: 29193801
    [TBL] [Abstract][Full Text] [Related]  

  • 8. [Meta-analysis of the Italian studies on short-term effects of air pollution].
    Biggeri A; Bellini P; Terracini B;
    Epidemiol Prev; 2001; 25(2 Suppl):1-71. PubMed ID: 11515188
    [TBL] [Abstract][Full Text] [Related]  

  • 9. Predictive P-score for treatment ranking in Bayesian network meta-analysis.
    Rosenberger KJ; Duan R; Chen Y; Lin L
    BMC Med Res Methodol; 2021 Oct; 21(1):213. PubMed ID: 34657593
    [TBL] [Abstract][Full Text] [Related]  

  • 10. An empirical comparison of Bayesian modelling strategies for missing binary outcome data in network meta-analysis.
    Spineli LM
    BMC Med Res Methodol; 2019 Apr; 19(1):86. PubMed ID: 31018836
    [TBL] [Abstract][Full Text] [Related]  

  • 11. Bayesian splines versus fractional polynomials in network meta-analysis.
    Heinecke A; Tallarita M; De Iorio M
    BMC Med Res Methodol; 2020 Oct; 20(1):261. PubMed ID: 33081698
    [TBL] [Abstract][Full Text] [Related]  

  • 12. Multivariate network meta-analysis of survival function parameters.
    Cope S; Chan K; Jansen JP
    Res Synth Methods; 2020 May; 11(3):443-456. PubMed ID: 32125077
    [TBL] [Abstract][Full Text] [Related]  

  • 13. Bayesian meta-analysis using SAS PROC BGLIMM.
    Rott KW; Lin L; Hodges JS; Siegel L; Shi A; Chen Y; Chu H
    Res Synth Methods; 2021 Nov; 12(6):692-700. PubMed ID: 34245227
    [TBL] [Abstract][Full Text] [Related]  

  • 14. Diagnostics for generalized linear hierarchical models in network meta-analysis.
    Zhao H; Hodges JS; Carlin BP
    Res Synth Methods; 2017 Sep; 8(3):333-342. PubMed ID: 28683516
    [TBL] [Abstract][Full Text] [Related]  

  • 15. Model building in nonproportional hazard regression.
    Rodríguez-Girondo M; Kneib T; Cadarso-Suárez C; Abu-Assi E
    Stat Med; 2013 Dec; 32(30):5301-14. PubMed ID: 24038401
    [TBL] [Abstract][Full Text] [Related]  

  • 16. Using structural equation modeling for network meta-analysis.
    Tu YK; Wu YC
    BMC Med Res Methodol; 2017 Jul; 17(1):104. PubMed ID: 28709406
    [TBL] [Abstract][Full Text] [Related]  

  • 17. Participants' outcomes gone missing within a network of interventions: Bayesian modeling strategies.
    Spineli LM; Kalyvas C; Pateras K
    Stat Med; 2019 Sep; 38(20):3861-3879. PubMed ID: 31134664
    [TBL] [Abstract][Full Text] [Related]  

  • 18. Bayesian one-step IPD network meta-analysis of time-to-event data using Royston-Parmar models.
    Freeman SC; Carpenter JR
    Res Synth Methods; 2017 Dec; 8(4):451-464. PubMed ID: 28742955
    [TBL] [Abstract][Full Text] [Related]  

  • 19. Bayesian pairwise meta-analysis of time-to-event outcomes in the presence of non-proportional hazards: A simulation study of flexible parametric, piecewise exponential and fractional polynomial models.
    Freeman SC; Sutton AJ; Cooper NJ; Gasparini A; Crowther MJ; Hawkins N
    Res Synth Methods; 2024 May; ():. PubMed ID: 38772906
    [TBL] [Abstract][Full Text] [Related]  

  • 20. Statistical approaches for conducting network meta-analysis in drug development.
    Jones B; Roger J; Lane PW; Lawton A; Fletcher C; Cappelleri JC; Tate H; Moneuse P;
    Pharm Stat; 2011; 10(6):523-31. PubMed ID: 22213533
    [TBL] [Abstract][Full Text] [Related]  

    [Next]    [New Search]
    of 9.