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.
3. Power and sample size when multiple endpoints are considered. Senn S; Bretz F Pharm Stat; 2007; 6(3):161-70. PubMed ID: 17674404 [TBL] [Abstract][Full Text] [Related]
4. Interpretation of research data: hypothesis testing. Stolar MH Am J Hosp Pharm; 1980 Nov; 37(11):1539-45. PubMed ID: 7211860 [TBL] [Abstract][Full Text] [Related]
5. Proper interpretation of non-differential misclassification effects: expectations vs observations. Jurek AM; Greenland S; Maldonado G; Church TR Int J Epidemiol; 2005 Jun; 34(3):680-7. PubMed ID: 15802377 [TBL] [Abstract][Full Text] [Related]
6. Empirical Bayes adjustments for multiple results in hypothesis-generating or surveillance studies. Steenland K; Bray I; Greenland S; Boffetta P Cancer Epidemiol Biomarkers Prev; 2000 Sep; 9(9):895-903. PubMed ID: 11008906 [TBL] [Abstract][Full Text] [Related]
7. [How to assess the size of a clinical trial?]. Paesmans M Rev Mal Respir; 1994; 11(6):547-57. PubMed ID: 7831504 [TBL] [Abstract][Full Text] [Related]
8. Multiple comparisons distortions of parameter estimates. Jeffries NO Biostatistics; 2007 Apr; 8(2):500-4. PubMed ID: 16971376 [TBL] [Abstract][Full Text] [Related]
9. Quantile-function based null distribution in resampling based multiple testing. van der Laan MJ; Hubbard AE Stat Appl Genet Mol Biol; 2006; 5():Article14. PubMed ID: 17049025 [TBL] [Abstract][Full Text] [Related]
10. Redressing the power and effect of significance. A new approach to an old problem: teaching statistics to nursing students. Taylor S; Muncer S Nurse Educ Today; 2000 Jul; 20(5):358-64. PubMed ID: 10895117 [TBL] [Abstract][Full Text] [Related]
11. Empirical Bayes screening of many p-values with applications to microarray studies. Datta S; Datta S Bioinformatics; 2005 May; 21(9):1987-94. PubMed ID: 15691856 [TBL] [Abstract][Full Text] [Related]
12. Applying the law of iterated logarithm to control type I error in cumulative meta-analysis of binary outcomes. Hu M; Cappelleri JC; Lan KK Clin Trials; 2007; 4(4):329-40. PubMed ID: 17848494 [TBL] [Abstract][Full Text] [Related]
13. How can I deal with missing data in my study? Bennett DA Aust N Z J Public Health; 2001 Oct; 25(5):464-9. PubMed ID: 11688629 [TBL] [Abstract][Full Text] [Related]
14. Statistical inference by confidence intervals: issues of interpretation and utilization. Sim J; Reid N Phys Ther; 1999 Feb; 79(2):186-95. PubMed ID: 10029058 [TBL] [Abstract][Full Text] [Related]
15. Bias in error estimation when using cross-validation for model selection. Varma S; Simon R BMC Bioinformatics; 2006 Feb; 7():91. PubMed ID: 16504092 [TBL] [Abstract][Full Text] [Related]
16. [Popper and the problem of induction in epidemiology]. Banegas JR; RodrÃguez Artalejo F; del Rey Calero J Rev Esp Salud Publica; 2000; 74(4):327-39. PubMed ID: 11031841 [TBL] [Abstract][Full Text] [Related]
17. Imputation strategies for blood pressure data nonignorably missing due to medication use. Cook NR Clin Trials; 2006; 3(5):411-20. PubMed ID: 17060215 [TBL] [Abstract][Full Text] [Related]
18. Multiple imputation for body mass index: lessons from the Australian Longitudinal Study on Women's Health. Mishra GD; Dobson AJ Stat Med; 2004 Oct; 23(19):3077-87. PubMed ID: 15351961 [TBL] [Abstract][Full Text] [Related]
19. Multiplicity and flexibility in clinical trials. Brannath W; Koenig F; Bauer P Pharm Stat; 2007; 6(3):205-16. PubMed ID: 17674349 [TBL] [Abstract][Full Text] [Related]