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 *

144 related articles for article (PubMed ID: 35861621)

  • 1. Designing three-level cluster randomized trials to assess treatment effect heterogeneity.
    Li F; Chen X; Tian Z; Esserman D; Heagerty PJ; Wang R
    Biostatistics; 2023 Oct; 24(4):833-849. PubMed ID: 35861621
    [TBL] [Abstract][Full Text] [Related]  

  • 2. Planning stepped wedge cluster randomized trials to detect treatment effect heterogeneity.
    Li F; Chen X; Tian Z; Wang R; Heagerty PJ
    Stat Med; 2024 Feb; 43(5):890-911. PubMed ID: 38115805
    [TBL] [Abstract][Full Text] [Related]  

  • 3. Folic acid supplementation and malaria susceptibility and severity among people taking antifolate antimalarial drugs in endemic areas.
    Crider K; Williams J; Qi YP; Gutman J; Yeung L; Mai C; Finkelstain J; Mehta S; Pons-Duran C; Menéndez C; Moraleda C; Rogers L; Daniels K; Green P
    Cochrane Database Syst Rev; 2022 Feb; 2(2022):. PubMed ID: 36321557
    [TBL] [Abstract][Full Text] [Related]  

  • 4. Sample size considerations for assessing treatment effect heterogeneity in randomized trials with heterogeneous intracluster correlations and variances.
    Tong G; Taljaard M; Li F
    Stat Med; 2023 Aug; 42(19):3392-3412. PubMed ID: 37316956
    [TBL] [Abstract][Full Text] [Related]  

  • 5. Sample size requirements for testing treatment effect heterogeneity in cluster randomized trials with binary outcomes.
    Maleyeff L; Wang R; Haneuse S; Li F
    Stat Med; 2023 Nov; 42(27):5054-5083. PubMed ID: 37974475
    [TBL] [Abstract][Full Text] [Related]  

  • 6. Sample size and power calculation for testing treatment effect heterogeneity in cluster randomized crossover designs.
    Wang X; Chen X; Goldfeld KS; Taljaard M; Li F
    Stat Methods Med Res; 2024 Jul; 33(7):1115-1136. PubMed ID: 38689556
    [TBL] [Abstract][Full Text] [Related]  

  • 7. Power considerations for generalized estimating equations analyses of four-level cluster randomized trials.
    Wang X; Turner EL; Preisser JS; Li F
    Biom J; 2022 Apr; 64(4):663-680. PubMed ID: 34897793
    [TBL] [Abstract][Full Text] [Related]  

  • 8. swdpwr: A SAS macro and an R package for power calculations in stepped wedge cluster randomized trials.
    Chen J; Zhou X; Li F; Spiegelman D
    Comput Methods Programs Biomed; 2022 Jan; 213():106522. PubMed ID: 34818620
    [TBL] [Abstract][Full Text] [Related]  

  • 9. Accounting for unequal cluster sizes in designing cluster randomized trials to detect treatment effect heterogeneity.
    Tong G; Esserman D; Li F
    Stat Med; 2022 Apr; 41(8):1376-1396. PubMed ID: 34923655
    [TBL] [Abstract][Full Text] [Related]  

  • 10. Designing multicenter individually randomized group treatment trials.
    Tong G; Tong J; Li F
    Biom J; 2024 Jan; 66(1):e2200307. PubMed ID: 37768850
    [TBL] [Abstract][Full Text] [Related]  

  • 11. A readily available improvement over method of moments for intra-cluster correlation estimation in the context of cluster randomized trials and fitting a GEE-type marginal model for binary outcomes.
    Westgate PM
    Clin Trials; 2019 Feb; 16(1):41-51. PubMed ID: 30295512
    [TBL] [Abstract][Full Text] [Related]  

  • 12. Impact of complex, partially nested clustering in a three-arm individually randomized group treatment trial: A case study with the wHOPE trial.
    Tong G; Seal KH; Becker WC; Li F; Dziura JD; Peduzzi PN; Esserman DA
    Clin Trials; 2022 Feb; 19(1):3-13. PubMed ID: 34693748
    [TBL] [Abstract][Full Text] [Related]  

  • 13. Power and sample size calculations for cluster randomized trials with binary outcomes when intracluster correlation coefficients vary by treatment arm.
    Kennedy-Shaffer L; Hughes MD
    Clin Trials; 2022 Feb; 19(1):42-51. PubMed ID: 34879711
    [TBL] [Abstract][Full Text] [Related]  

  • 14. Sample size requirements for detecting treatment effect heterogeneity in cluster randomized trials.
    Yang S; Li F; Starks MA; Hernandez AF; Mentz RJ; Choudhury KR
    Stat Med; 2020 Dec; 39(28):4218-4237. PubMed ID: 32823372
    [TBL] [Abstract][Full Text] [Related]  

  • 15. Accounting for expected attrition in the planning of cluster randomized trials for assessing treatment effect heterogeneity.
    Tong J; Li F; Harhay MO; Tong G
    BMC Med Res Methodol; 2023 Apr; 23(1):85. PubMed ID: 37024809
    [TBL] [Abstract][Full Text] [Related]  

  • 16. Hierarchical Bayesian modeling of heterogeneous outcome variance in cluster randomized trials.
    Tong G; Tong J; Jiang Y; Esserman D; Harhay MO; Warren JL
    Clin Trials; 2024 Aug; 21(4):451-460. PubMed ID: 38197388
    [TBL] [Abstract][Full Text] [Related]  

  • 17. Maximin optimal cluster randomized designs for assessing treatment effect heterogeneity.
    Ryan MM; Esserman D; Li F
    Stat Med; 2023 Sep; 42(21):3764-3785. PubMed ID: 37339777
    [TBL] [Abstract][Full Text] [Related]  

  • 18. Appropriate statistical methods for analysing partially nested randomised controlled trials with continuous outcomes: a simulation study.
    Candlish J; Teare MD; Dimairo M; Flight L; Mandefield L; Walters SJ
    BMC Med Res Methodol; 2018 Oct; 18(1):105. PubMed ID: 30314463
    [TBL] [Abstract][Full Text] [Related]  

  • 19. Sample size estimation for modified Poisson analysis of cluster randomized trials with a binary outcome.
    Li F; Tong G
    Stat Methods Med Res; 2021 May; 30(5):1288-1305. PubMed ID: 33826454
    [TBL] [Abstract][Full Text] [Related]  

  • 20. Sample size calculation in three-level cluster randomized trials using generalized estimating equation models.
    Liu J; Colditz GA
    Stat Med; 2020 Oct; 39(24):3347-3372. PubMed ID: 32720717
    [TBL] [Abstract][Full Text] [Related]  

    [Next]    [New Search]
    of 8.