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 *

320 related articles for article (PubMed ID: 28202011)

  • 21. Quantifying heterogeneity in individual participant data meta-analysis with binary outcomes.
    Chen B; Benedetti A
    Syst Rev; 2017 Dec; 6(1):243. PubMed ID: 29208048
    [TBL] [Abstract][Full Text] [Related]  

  • 22. An evaluation of statistical approaches for analyzing physician-randomized quality improvement interventions.
    Stedman MR; Gagnon DR; Lew RA; Solomon DH; Brookhart MA
    Contemp Clin Trials; 2008 Sep; 29(5):687-95. PubMed ID: 18571476
    [TBL] [Abstract][Full Text] [Related]  

  • 23. Random Effects Multinomial Processing Tree Models: A Maximum Likelihood Approach.
    Nestler S; Erdfelder E
    Psychometrika; 2023 Sep; 88(3):809-829. PubMed ID: 37247167
    [TBL] [Abstract][Full Text] [Related]  

  • 24. Strategies for analyzing multilevel cluster-randomized studies with binary outcomes collected at varying intervals of time.
    Olsen MK; DeLong ER; Oddone EZ; Bosworth HB
    Stat Med; 2008 Dec; 27(29):6055-71. PubMed ID: 18825655
    [TBL] [Abstract][Full Text] [Related]  

  • 25. A simulation study to assess statistical methods for binary repeated measures data.
    Masaoud E; Stryhn H
    Prev Vet Med; 2010 Feb; 93(2-3):81-97. PubMed ID: 20004989
    [TBL] [Abstract][Full Text] [Related]  

  • 26. Meta-analysis of studies with bivariate binary outcomes: a marginal beta-binomial model approach.
    Chen Y; Hong C; Ning Y; Su X
    Stat Med; 2016 Jan; 35(1):21-40. PubMed ID: 26303591
    [TBL] [Abstract][Full Text] [Related]  

  • 27. Meta-analysis of binary data: which within study variance estimate to use?
    Chang BH; Waternaux C; Lipsitz S
    Stat Med; 2001 Jul; 20(13):1947-56. PubMed ID: 11427951
    [TBL] [Abstract][Full Text] [Related]  

  • 28. Two-stage methods for the analysis of pooled data.
    Stukel TA; Demidenko E; Dykes J; Karagas MR
    Stat Med; 2001 Jul; 20(14):2115-30. PubMed ID: 11439425
    [TBL] [Abstract][Full Text] [Related]  

  • 29. Estimating relative risks in multicenter studies with a small number of centers - which methods to use? A simulation study.
    Pedroza C; Truong VTT
    Trials; 2017 Nov; 18(1):512. PubMed ID: 29096682
    [TBL] [Abstract][Full Text] [Related]  

  • 30. Comparing methods to estimate treatment effects on a continuous outcome in multicentre randomized controlled trials: a simulation study.
    Chu R; Thabane L; Ma J; Holbrook A; Pullenayegum E; Devereaux PJ
    BMC Med Res Methodol; 2011 Feb; 11():21. PubMed ID: 21338524
    [TBL] [Abstract][Full Text] [Related]  

  • 31. Logistic Regression with Multiple Random Effects: A Simulation Study of Estimation Methods and Statistical Packages.
    Kim Y; Choi YK; Emery S
    Am Stat; 2013 Aug; 67(3):. PubMed ID: 24288415
    [TBL] [Abstract][Full Text] [Related]  

  • 32. One-stage random effects meta-analysis using linear mixed models for aggregate continuous outcome data.
    Papadimitropoulou K; Stijnen T; Dekkers OM; le Cessie S
    Res Synth Methods; 2019 Sep; 10(3):360-375. PubMed ID: 30523676
    [TBL] [Abstract][Full Text] [Related]  

  • 33. Systematic review of methods for individual patient data meta- analysis with binary outcomes.
    Thomas D; Radji S; Benedetti A
    BMC Med Res Methodol; 2014 Jun; 14():79. PubMed ID: 24943877
    [TBL] [Abstract][Full Text] [Related]  

  • 34. Estimation using penalized quasilikelihood and quasi-pseudo-likelihood in Poisson mixed models.
    Lin X
    Lifetime Data Anal; 2007 Dec; 13(4):533-44. PubMed ID: 18080833
    [TBL] [Abstract][Full Text] [Related]  

  • 35. Generalized survival models for correlated time-to-event data.
    Liu XR; Pawitan Y; Clements MS
    Stat Med; 2017 Dec; 36(29):4743-4762. PubMed ID: 28905409
    [TBL] [Abstract][Full Text] [Related]  

  • 36. Bias correction in random effects models with sparse binary responses.
    Korre AK; Vasdekis VG
    Stat Methods Med Res; 2023 Nov; 32(11):2226-2239. PubMed ID: 37776847
    [TBL] [Abstract][Full Text] [Related]  

  • 37. When does the use of individual patient data in network meta-analysis make a difference? A simulation study.
    Kanters S; Karim ME; Thorlund K; Anis A; Bansback N
    BMC Med Res Methodol; 2021 Jan; 21(1):21. PubMed ID: 33435879
    [TBL] [Abstract][Full Text] [Related]  

  • 38. High performance implementation of the hierarchical likelihood for generalized linear mixed models: an application to estimate the potassium reference range in massive electronic health records datasets.
    Bologa CG; Pankratz VS; Unruh ML; Roumelioti ME; Shah V; Shaffi SK; Arzhan S; Cook J; Argyropoulos C
    BMC Med Res Methodol; 2021 Jul; 21(1):151. PubMed ID: 34303362
    [TBL] [Abstract][Full Text] [Related]  

  • 39. Estimating heterogeneity in random effects models for longitudinal data.
    Lemenuel-Diot A; Mallet A; Laveille C; Bruno R
    Biom J; 2005 Jun; 47(3):329-45. PubMed ID: 16053257
    [TBL] [Abstract][Full Text] [Related]  

  • 40. Individual participant data meta-analysis for a binary outcome: one-stage or two-stage?
    Debray TP; Moons KG; Abo-Zaid GM; Koffijberg H; Riley RD
    PLoS One; 2013; 8(4):e60650. PubMed ID: 23585842
    [TBL] [Abstract][Full Text] [Related]  

    [Previous]   [Next]    [New Search]
    of 16.