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 *

133 related articles for article (PubMed ID: 34668458)

  • 1. Estimating the sample mean and standard deviation from order statistics and sample size in meta-analysis.
    Cai S; Zhou J; Pan J
    Stat Methods Med Res; 2021 Dec; 30(12):2701-2719. PubMed ID: 34668458
    [TBL] [Abstract][Full Text] [Related]  

  • 2. ABCMETAapp: R shiny application for simulation-based estimation of mean and standard deviation for meta-analysis via approximate Bayesian computation.
    Kwon D; Reddy RRS; Reis IM
    Res Synth Methods; 2021 Nov; 12(6):842-848. PubMed ID: 34148300
    [TBL] [Abstract][Full Text] [Related]  

  • 3. Simulation-based estimation of mean and standard deviation for meta-analysis via Approximate Bayesian Computation (ABC).
    Kwon D; Reis IM
    BMC Med Res Methodol; 2015 Aug; 15():61. PubMed ID: 26264850
    [TBL] [Abstract][Full Text] [Related]  

  • 4. Estimating the sample mean and standard deviation from the sample size, median, range and/or interquartile range.
    Wan X; Wang W; Liu J; Tong T
    BMC Med Res Methodol; 2014 Dec; 14():135. PubMed ID: 25524443
    [TBL] [Abstract][Full Text] [Related]  

  • 5. Estimating the sample mean and standard deviation from commonly reported quantiles in meta-analysis.
    McGrath S; Zhao X; Steele R; Thombs BD; Benedetti A;
    Stat Methods Med Res; 2020 Sep; 29(9):2520-2537. PubMed ID: 32292115
    [TBL] [Abstract][Full Text] [Related]  

  • 6. Standard error estimation in meta-analysis of studies reporting medians.
    McGrath S; Katzenschlager S; Zimmer AJ; Seitel A; Steele R; Benedetti A
    Stat Methods Med Res; 2023 Feb; 32(2):373-388. PubMed ID: 36412105
    [TBL] [Abstract][Full Text] [Related]  

  • 7. Optimally estimating the sample standard deviation from the five-number summary.
    Shi J; Luo D; Weng H; Zeng XT; Lin L; Chu H; Tong T
    Res Synth Methods; 2020 Sep; 11(5):641-654. PubMed ID: 32562361
    [TBL] [Abstract][Full Text] [Related]  

  • 8. Optimally estimating the sample mean from the sample size, median, mid-range, and/or mid-quartile range.
    Luo D; Wan X; Liu J; Tong T
    Stat Methods Med Res; 2018 Jun; 27(6):1785-1805. PubMed ID: 27683581
    [TBL] [Abstract][Full Text] [Related]  

  • 9. A random effects meta-analysis model with Box-Cox transformation.
    Yamaguchi Y; Maruo K; Partlett C; Riley RD
    BMC Med Res Methodol; 2017 Jul; 17(1):109. PubMed ID: 28724350
    [TBL] [Abstract][Full Text] [Related]  

  • 10. One-sample aggregate data meta-analysis of medians.
    McGrath S; Zhao X; Qin ZZ; Steele R; Benedetti A
    Stat Med; 2019 Mar; 38(6):969-984. PubMed ID: 30460713
    [TBL] [Abstract][Full Text] [Related]  

  • 11. Estimating the mean and variance from the median, range, and the size of a sample.
    Hozo SP; Djulbegovic B; Hozo I
    BMC Med Res Methodol; 2005 Apr; 5():13. PubMed ID: 15840177
    [TBL] [Abstract][Full Text] [Related]  

  • 12. Detecting the skewness of data from the five-number summary and its application in meta-analysis.
    Shi J; Luo D; Wan X; Liu Y; Liu J; Bian Z; Tong T
    Stat Methods Med Res; 2023 Jul; 32(7):1338-1360. PubMed ID: 37161735
    [TBL] [Abstract][Full Text] [Related]  

  • 13. Meta-analysis of the difference of medians.
    McGrath S; Sohn H; Steele R; Benedetti A
    Biom J; 2020 Jan; 62(1):69-98. PubMed ID: 31553488
    [TBL] [Abstract][Full Text] [Related]  

  • 14. Meta-analysis without study-specific variance information: Heterogeneity case.
    Sangnawakij P; Böhning D; Niwitpong SA; Adams S; Stanton M; Holling H
    Stat Methods Med Res; 2019 Jan; 28(1):196-210. PubMed ID: 28681700
    [TBL] [Abstract][Full Text] [Related]  

  • 15. Estimating the mean and standard deviation of environmental data with below detection limit observations: Considering highly skewed data and model misspecification.
    Shoari N; Dubé JS; Chenouri S
    Chemosphere; 2015 Nov; 138():599-608. PubMed ID: 26210025
    [TBL] [Abstract][Full Text] [Related]  

  • 16. Estimation of population parameters using sample extremes from nonconstant sample sizes.
    Kolba TN; Bruno A
    PLoS One; 2023; 18(1):e0280561. PubMed ID: 36662707
    [TBL] [Abstract][Full Text] [Related]  

  • 17. Parametric and nonparametric population methods: their comparative performance in analysing a clinical dataset and two Monte Carlo simulation studies.
    Bustad A; Terziivanov D; Leary R; Port R; Schumitzky A; Jelliffe R
    Clin Pharmacokinet; 2006; 45(4):365-83. PubMed ID: 16584284
    [TBL] [Abstract][Full Text] [Related]  

  • 18. The use of bootstrap methods for estimating sample size and analysing health-related quality of life outcomes.
    Walters SJ; Campbell MJ
    Stat Med; 2005 Apr; 24(7):1075-102. PubMed ID: 15570625
    [TBL] [Abstract][Full Text] [Related]  

  • 19. Explorations in statistics: the log transformation.
    Curran-Everett D
    Adv Physiol Educ; 2018 Jun; 42(2):343-347. PubMed ID: 29761718
    [TBL] [Abstract][Full Text] [Related]  

  • 20. Effect of Box-Cox transformation on power of Haseman-Elston and maximum-likelihood variance components tests to detect quantitative trait Loci.
    Etzel CJ; Shete S; Beasley TM; Fernandez JR; Allison DB; Amos CI
    Hum Hered; 2003; 55(2-3):108-16. PubMed ID: 12931049
    [TBL] [Abstract][Full Text] [Related]  

    [Next]    [New Search]
    of 7.