BIOMARKERS

Molecular Biopsy of Human Tumors

- a resource for Precision Medicine *

136 related articles for article (PubMed ID: 14664685)

  • 1. Power and measures of effect size in analysis of variance with fixed versus random nested factors.
    Siemer M; Joormann J
    Psychol Methods; 2003 Dec; 8(4):497-517. PubMed ID: 14664685
    [TBL] [Abstract][Full Text] [Related]  

  • 2. Assumptions and consequences of treating providers in therapy studies as fixed versus random effects: reply to Crits-Christoph, Tu, and Gallop (2003) and Serlin, Wampold, and Levin (2003).
    Siemer M; Joormann J
    Psychol Methods; 2003 Dec; 8(4):535-44. PubMed ID: 14664688
    [TBL] [Abstract][Full Text] [Related]  

  • 3. Should providers of treatment be regarded as a random factor? If it ain't broke, don't "fix" it: a comment on Siemer and Joormann (2003).
    Serlin RC; Wampold BE; Levin JR
    Psychol Methods; 2003 Dec; 8(4):524-34. PubMed ID: 14664687
    [TBL] [Abstract][Full Text] [Related]  

  • 4. Therapists as fixed versus random effects-some statistical and conceptual issues: a comment on Siemer and Joormann (2003).
    Crits-Christoph P; Tu X; Gallop R
    Psychol Methods; 2003 Dec; 8(4):518-23. PubMed ID: 14664686
    [TBL] [Abstract][Full Text] [Related]  

  • 5. The impact of omitting the interaction between crossed factors in cross-classified random effects modelling.
    Shi Y; Leite W; Algina J
    Br J Math Stat Psychol; 2010 Feb; 63(Pt 1):1-15. PubMed ID: 19243680
    [TBL] [Abstract][Full Text] [Related]  

  • 6. The analysis of continuous outcomes in multi-centre trials with small centre sizes.
    Pickering RM; Weatherall M
    Stat Med; 2007 Dec; 26(30):5445-56. PubMed ID: 17924360
    [TBL] [Abstract][Full Text] [Related]  

  • 7. A priori power analysis in longitudinal three-level multilevel models: an example with therapist effects.
    de Jong K; Moerbeek M; van der Leeden R
    Psychother Res; 2010 May; 20(3):273-84. PubMed ID: 19946814
    [TBL] [Abstract][Full Text] [Related]  

  • 8. Hypothesis tests for population heterogeneity in meta-analysis.
    Viechtbauer W
    Br J Math Stat Psychol; 2007 May; 60(Pt 1):29-60. PubMed ID: 17535578
    [TBL] [Abstract][Full Text] [Related]  

  • 9. The role of method in treatment effectiveness research: evidence from meta-analysis.
    Wilson DB; Lipsey MW
    Psychol Methods; 2001 Dec; 6(4):413-29. PubMed ID: 11778681
    [TBL] [Abstract][Full Text] [Related]  

  • 10. The consequence of ignoring a nested factor on measures of effect size in analysis of variance.
    Wampold BE; Serlin RC
    Psychol Methods; 2000 Dec; 5(4):425-33. PubMed ID: 11194206
    [TBL] [Abstract][Full Text] [Related]  

  • 11. A comparison of the statistical power of different methods for the analysis of cluster randomization trials with binary outcomes.
    Austin PC
    Stat Med; 2007 Aug; 26(19):3550-65. PubMed ID: 17238238
    [TBL] [Abstract][Full Text] [Related]  

  • 12. Powerful spin in the conclusion of Wampold et al.'s re-analysis of placebo versus no-treatment trials despite similar results as in original review.
    Hróbjartsson A; Gøtzsche PC
    J Clin Psychol; 2007 Apr; 63(4):373-7. PubMed ID: 17279532
    [TBL] [Abstract][Full Text] [Related]  

  • 13. Comparison of data analysis strategies for intent-to-treat analysis in pre-test-post-test designs with substantial dropout rates.
    Salim A; Mackinnon A; Christensen H; Griffiths K
    Psychiatry Res; 2008 Sep; 160(3):335-45. PubMed ID: 18718673
    [TBL] [Abstract][Full Text] [Related]  

  • 14. 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]  

  • 15. Analysis of variance frameworks in clinical child and adolescent psychology: issues and recommendations.
    Jaccard J; Guilamo-Ramos V
    J Clin Child Adolesc Psychol; 2002 Mar; 31(1):130-46. PubMed ID: 11845645
    [TBL] [Abstract][Full Text] [Related]  

  • 16. Power to detect homework effects in psychotherapy outcome research.
    Kazantzis N
    J Consult Clin Psychol; 2000 Feb; 68(1):166-70. PubMed ID: 10710851
    [TBL] [Abstract][Full Text] [Related]  

  • 17. Who is the marginal patient? Understanding instrumental variables estimates of treatment effects.
    Harris KM; Remler DK
    Health Serv Res; 1998 Dec; 33(5 Pt 1):1337-60. PubMed ID: 9865223
    [TBL] [Abstract][Full Text] [Related]  

  • 18. Using analysis of covariance (ANCOVA) with fallible covariates.
    Culpepper SA; Aguinis H
    Psychol Methods; 2011 Jun; 16(2):166-78. PubMed ID: 21517178
    [TBL] [Abstract][Full Text] [Related]  

  • 19. Optimum sample size allocation to minimize cost or maximize power for the two-sample trimmed mean test.
    Guo JH; Luh WM
    Br J Math Stat Psychol; 2009 May; 62(Pt 2):283-98. PubMed ID: 18157920
    [TBL] [Abstract][Full Text] [Related]  

  • 20. The metric comparability of meta-analytic effect-size estimators from factorial designs.
    Gillett R
    Psychol Methods; 2003 Dec; 8(4):419-33. PubMed ID: 14664680
    [TBL] [Abstract][Full Text] [Related]  

    [Next]    [New Search]
    of 7.