Power and sample size calculations for the Wilcoxon-Mann-Whitney test in the presence of death-censored observations

Statistics in Medicine

Volumn 34, Issue 3, 2015, Pages 406-431

  Matsouaka, Roland A ^a   Betensky, Rebecca A ^a  

^a HARVARD SCHOOL OF PUBLIC HEALTH   (United States)

Author keywords

Composite outcome; Informative missingness; Intention to treat; Worst rank scores, Wilcoxon rank sum test

Indexed keywords

ACCURACY; ARTICLE; DEATH CENSORED OBSERVATION; DISEASE COURSE; FOLLOW UP; HUMAN; MONTE CARLO METHOD; OBSERVATION; RANK SUM TEST; SAMPLE SIZE; SCORING SYSTEM; STATISTICAL ANALYSIS; SURVIVAL; TIME OF DEATH; COMPUTER SIMULATION; MORTALITY; NONPARAMETRIC TEST; RANDOMIZED CONTROLLED TRIAL (TOPIC); STATISTICAL BIAS; STATISTICAL MODEL;

BIAS (EPIDEMIOLOGY); COMPUTER SIMULATION; MODELS, STATISTICAL; MONTE CARLO METHOD; MORTALITY; RANDOMIZED CONTROLLED TRIALS AS TOPIC; SAMPLE SIZE; STATISTICS, NONPARAMETRIC;

EID: 84920742395     PISSN: 02776715     EISSN: 10970258     Source Type: Journal    
DOI: 10.1002/sim.6355     Document Type: Article

References (44)

1. Zhang JL, Rubin DB. Estimation of causal effects via principal stratification when some outcomes are truncated by death. Journal of Educational and Behavioral Statistics 2003; 28(4):353-368.
2. Rubin DB. Causal inference through potential outcomes and principal stratification: application to studies with "censoring" due to death. Statistical Science 2006; 299-309.
3. Frangakis CE, Rubin DB. Principal stratification in causal inference. Biometrics 2002; 58(1):21-29.
4. Singhal A. Normobaric Oxygen Therapy in Acute Ischemic Stroke Trial. ClinicalTrials.gov Database December 2006. (Available from: http://clinicaltrials.gov/ct2/show/NCT00414726) [Accessed on 4 November 2014].
5. Singhal A, Benner T, Roccatagliata L, Koroshetz W, Schaefer P, Lo E, Buonanno F, Gonzalez R, Sorensen A. A pilot study of normobaric oxygen therapy in acute ischemic stroke. Stroke 2005; 36(4):797.
6. Kumar S, Selim M, Caplan L. Medical complications after stroke. The Lancet Neurology 2010; 9(1):105-118.
7. Lachin J. Worst-rank score analysis with informatively missing observations in clinical trials. Controlled Clinical Trials 1999; 20(5):408-422.
8. Berry JD, Miller R, Moore DH, Cudkowicz ME, Van DenBerg LH, Kerr DA, Dong Y, Ingersoll EW, Archibald D. The Combined Assessment of Function and Survival (CAFS): a new endpoint for ALS clinical trials. Amyotrophic Lateral Sclerosis and Frontotemporal Degeneration 2013; 14(3):162-168.
9. Felker G, Maisel A. A global rank end point for clinical trials in acute heart failure. Circulation: Heart Failure 2010; 3(5):643-646.
10. Neaton JD, Wentworth DN, Rhame F, Hogan C, Abrams DI, Deyton L. Considerations in choice of a clinical endpoint for aids clinical trials. Statistics in Medicine 1994; 13(19-20):2107-2125.
11. Lisa AB, James SH. Rule-based ranking schemes for antiretroviral trials. Statistics in Medicine 1997; 16:1175-1191.
12. JoshuaChen YH, Gould AL, Nessly ML. Treatment comparisons for a partially categorical outcome applied to a biomarker with assay limit. Statistics in Medicine 2005; 24(2):211-228.
13. Follmann D, Wittes J, Cutler JA. The use of subjective rankings in clinical trials with an application to cardiovascular disease. Statistics in Medicine 1992; 11(4):427-437.
14. Brittain E, Palensky J, Blood J, Wittes J. Blinded subjective rankings as a method of assessing treatment effect: a large sample example from the systolic hypertension in the elderly program (shep). Statistics in Medicine 1997; 16(6):681-693.
15. Felker G, Anstrom K, Rogers J. A global ranking approach to end points in trials of mechanical circulatory support devices. Journal of Cardiac Failure 2008; 14(5):368-372.
16. Allen LA, Hernandez AF, O'Connor CM, Felker GM. End points for clinical trials in acute heart failure syndromes. Journal of the American College of Cardiology 2009; 53(24):2248-2258.
17. Allen LA, Spertus JA, et al. End points for comparative effectiveness research in heart failure. Heart Failure Clinics 2013; 9(1):15-28.
18. Sun H, Davison BA, Cotter G, Pencina MJ, Koch GG. Evaluating treatment efficacy by multiple end points in phase II acute heart failure clinical trials analyzing data using a global method. Circulation: Heart Failure 2012; 5(6):742-749.
19. Subherwal S, Anstrom KJ, Jones WS, Felker MG, Misra S, Conte MS, Hiatt WR, Patel MR. Use of alternative methodologies for evaluation of composite end points in trials of therapies for critical limb ischemia. American Heart Journal 2012; 164(3):277-284.
20. DeCoster T, Willis M, Marsh J, Williams T, Nepola J, Dirschl D, Hurwitz S. Rank order analysis of tibial plafond fractures: does injury or reduction predict outcome?Foot & Ankle International 1999; 20(1):44-49.
21. Gould A. A new approach to the analysis of clinical drug trials with withdrawals. Biometrics 1980; 36(4):721-727.
22. Ritchie J, Cerqueira M, Maynard C, Davis K, Kennedy J. Ventricular function and infarct size: the Western Washington intravenous streptokinase in myocardial infarction trial. Journal of the American College of Cardiology 1988; 11(4):689.
23. Ritchie J, Davis K, Williams D, Caldwell J, Kennedy J. Global and regional left ventricular function and tomographic radionuclide perfusion: the Western Washington Intracoronary Streptokinase in Myocardial Infarction Trial. Circulation 1984; 70(5):867.
24. Senn SS. Statistical Issues in Drug Development. Vol.69, John Wiley & Sons: Chichester, New York, 2008.
25. McMahon R, Harrell F, Jr. Power calculation for clinical trials when the outcome is a composite ranking of survival and a nonfatal outcome. Controlled Clinical Trials 2000; 21(4):305-312.
26. Shieh G, Jan S, Randles RH. On power and sample size determinations for the Wilcoxon-Mann-Whitney test. Nonparametric Statistics 2006; 18(1):33-43.
27. Lehmann EL, D'Abrera HJM. Nonparametrics: Statistical Methods Based on Ranks. Springer: New York, 2006.
28. Noether G. Sample size determination for some common nonparametric tests. Journal of the American Statistical Association 1987; 82(398):645-647.
29. Rosner B, Glynn R. Power and sample size estimation for the Wilcoxon rank sum test with application to comparisons of C statistics from alternative prediction models. Biometrics 2009; 65(1):188-197.
30. Wang H, Chen B, Chow S. Sample size determination based on rank tests in clinical trials. Journal of Biopharmaceutical Statistics 2003; 13(4):735-751.
31. Greene T, Joffe M, Hu B, Li L, Boucher K. The balanced survivor average causal effect. The International Journal of Biostatistics 2013; 9(2):291-306.
32. Siegel S, Castellan N Jr. Nonparametric Statistics for the Behavioral Sciences (2nd edn). McGraw-Hill Book Company: New York, 1988.
33. Bellera C, Julien M, Hanley J. Normal approximations to the distributions of the Wilcoxon statistics: accurate to what N? Graphical insights. Journal of Statistics Education 2010; 18(2.
34. Matsouaka R, Singhal A, Betensky R. The optimal Wilcoxon-Mann-Whitney test in the presence of death-censored observations. Submitted to Statistics in Medicine 2014.
35. Shih W. Problems in dealing with missing data and informative censoring in clinical trials. Current Controlled Trials in Cardiovascular Medicine 2002; 3(1):4.
36. Rosner B, Glynn RJ. Power and sample size estimation for the clustered Wilcoxon test. Biometrics 2011; 67(2):646-653.
37. Rahardja D, Zhao Y, Qu Y. Sample size determinations for the Wilcoxon-Mann-Whitney test: a comprehensive review. Statistics in Biopharmaceutical Research 2009; 1(3):317-322.
38. Zhao Y. Sample size estimation for the van Elteren test-a stratified Wilcoxon-Mann-Whitney test. Statistics in Medicine 2006; 25(15):2675-2687.
39. Wood A, White I, Thompson S. Are missing outcome data adequately handled? A review of published randomized controlled trials in major medical journals. Clinical Trials 2004; 1(4):368.
40. Armijo-Olivo S, Warren S, Magee D. Intention to treat analysis, compliance, drop-outs and how to deal with missing data in clinical research: a review. Physical Therapy Reviews 2009; 14(1):36-49.
41. Freeman BD, Danner RL, Banks SM, Natanson C. Safeguarding patients in clinical trials with high mortality rates. American Journal of Respiratory and Critical Care Medicine 2001; 164(2):190-192.
42. Moyé L, Davis B, Hawkins C. Analysis of a clinical trial involving a combined mortality and adherence dependent interval censored endpoint. Statistics in Medicine 1992; 11(13):1705-1717.
43. Moyé LA, Lai D, Jing K, Baraniuk MS, Kwak M, Penn MS, Wu CO. Combining censored and uncensored data in a U-statistic: design and sample size implications for cell therapy research. The International Journal of Biostatistics 2011; 7(1):1-29.
44. Finkelstein D, Schoenfeld D. Combining mortality and longitudinal measures in clinical trials. Statistics in Medicine 1999; 18(11):1341-1354.