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 *

365 related articles for article (PubMed ID: 26186114)

  • 1. Beyond Power Calculations: Assessing Type S (Sign) and Type M (Magnitude) Errors.
    Gelman A; Carlin J
    Perspect Psychol Sci; 2014 Nov; 9(6):641-51. PubMed ID: 26186114
    [TBL] [Abstract][Full Text] [Related]  

  • 2. Publication bias impacts on effect size, statistical power, and magnitude (Type M) and sign (Type S) errors in ecology and evolutionary biology.
    Yang Y; Sánchez-Tójar A; O'Dea RE; Noble DWA; Koricheva J; Jennions MD; Parker TH; Lagisz M; Nakagawa S
    BMC Biol; 2023 Apr; 21(1):71. PubMed ID: 37013585
    [TBL] [Abstract][Full Text] [Related]  

  • 3. Enhancing Statistical Inference in Psychological Research via Prospective and Retrospective Design Analysis.
    Altoè G; Bertoldo G; Zandonella Callegher C; Toffalini E; Calcagnì A; Finos L; Pastore M
    Front Psychol; 2019; 10():2893. PubMed ID: 31993004
    [TBL] [Abstract][Full Text] [Related]  

  • 4. Power, effects, confidence, and significance: an investigation of statistical practices in nursing research.
    Gaskin CJ; Happell B
    Int J Nurs Stud; 2014 May; 51(5):795-806. PubMed ID: 24207028
    [TBL] [Abstract][Full Text] [Related]  

  • 5. Reconsideration of the type I error rate for psychological science in the era of replication.
    Carlin MT; Costello MS; Flansburg MA; Darden A
    Psychol Methods; 2024 Apr; 29(2):379-387. PubMed ID: 35404627
    [TBL] [Abstract][Full Text] [Related]  

  • 6. The unappreciated heterogeneity of effect sizes: Implications for power, precision, planning of research, and replication.
    Kenny DA; Judd CM
    Psychol Methods; 2019 Oct; 24(5):578-589. PubMed ID: 30742474
    [TBL] [Abstract][Full Text] [Related]  

  • 7. A note on Type S/M errors in hypothesis testing.
    Lu J; Qiu Y; Deng A
    Br J Math Stat Psychol; 2019 Feb; 72(1):1-17. PubMed ID: 29569719
    [TBL] [Abstract][Full Text] [Related]  

  • 8. Underappreciated problems of low replication in ecological field studies.
    Lemoine NP; Hoffman A; Felton AJ; Baur L; Chaves F; Gray J; Yu Q; Smith MD
    Ecology; 2016 Oct; 97(10):2554-2561. PubMed ID: 27859125
    [TBL] [Abstract][Full Text] [Related]  

  • 9. Addressing the "Replication Crisis": Using Original Studies to Design Replication Studies with Appropriate Statistical Power.
    Anderson SF; Maxwell SE
    Multivariate Behav Res; 2017; 52(3):305-324. PubMed ID: 28266872
    [TBL] [Abstract][Full Text] [Related]  

  • 10. The statistical properties of RCTs and a proposal for shrinkage.
    van Zwet E; Schwab S; Senn S
    Stat Med; 2021 Nov; 40(27):6107-6117. PubMed ID: 34425632
    [TBL] [Abstract][Full Text] [Related]  

  • 11. The Failure of Null Hypothesis Significance Testing When Studying Incremental Changes, and What to Do About It.
    Gelman A
    Pers Soc Psychol Bull; 2018 Jan; 44(1):16-23. PubMed ID: 28914154
    [TBL] [Abstract][Full Text] [Related]  

  • 12. Statistical Power in Plant Pathology Research.
    Gent DH; Esker PD; Kriss AB
    Phytopathology; 2018 Jan; 108(1):15-22. PubMed ID: 28876210
    [TBL] [Abstract][Full Text] [Related]  

  • 13. Making reliable decisions in the study of wildlife diseases: using hypothesis tests, statistical power, and observed effects.
    O'Brien C; van Riper C; Myers DE
    J Wildl Dis; 2009 Jul; 45(3):700-12. PubMed ID: 19617480
    [TBL] [Abstract][Full Text] [Related]  

  • 14. On Attenuated Interactions, Measurement Error, and Statistical Power: Guidelines for Social and Personality Psychologists.
    Blake KR; Gangestad S
    Pers Soc Psychol Bull; 2020 Dec; 46(12):1702-1711. PubMed ID: 32208875
    [TBL] [Abstract][Full Text] [Related]  

  • 15. Controlling decision errors with minimal costs: The sequential probability ratio t test.
    Schnuerch M; Erdfelder E
    Psychol Methods; 2020 Apr; 25(2):206-226. PubMed ID: 31497982
    [TBL] [Abstract][Full Text] [Related]  

  • 16. Significance, Errors, Power, and Sample Size: The Blocking and Tackling of Statistics.
    Mascha EJ; Vetter TR
    Anesth Analg; 2018 Feb; 126(2):691-698. PubMed ID: 29346210
    [TBL] [Abstract][Full Text] [Related]  

  • 17. The experimental design of postmortem studies: the effect size and statistical power.
    Meurs J
    Forensic Sci Med Pathol; 2016 Sep; 12(3):343-9. PubMed ID: 27412160
    [TBL] [Abstract][Full Text] [Related]  

  • 18. A Meta-Meta-Analysis: Empirical Review of Statistical Power, Type I Error Rates, Effect Sizes, and Model Selection of Meta-Analyses Published in Psychology.
    Cafri G; Kromrey JD; Brannick MT
    Multivariate Behav Res; 2010 Mar; 45(2):239-70. PubMed ID: 26760285
    [TBL] [Abstract][Full Text] [Related]  

  • 19. Understanding statistical power.
    Norton BJ; Strube MJ
    J Orthop Sports Phys Ther; 2001 Jun; 31(6):307-15. PubMed ID: 11411625
    [TBL] [Abstract][Full Text] [Related]  

  • 20. [What to do if statistical power is low? A practical strategy for pre-post-designs].
    Müller J; Manz R; Hoyer J
    Psychother Psychosom Med Psychol; 2002; 52(9-10):408-16. PubMed ID: 12355348
    [TBL] [Abstract][Full Text] [Related]  

    [Next]    [New Search]
    of 19.