Information-based sample size re-estimation in group sequential design for longitudinal trials

Statistics in Medicine

Volumn 33, Issue 22, 2014, Pages 3801-3814

  Zhou, Jing ^a   Adewale, Adeniyi ^b   Shentu, Yue ^b   Liu, Jiajun ^b   Anderson, Keaven ^b  

^a University of North Carolina at Chapel Hill   (United States)

^b MERCK RESEARCH LABORATORIES   (United States)

Author keywords

Adaptive design; Group sequential design; Information; Longitudinal data analysis; Sample size re estimation

Indexed keywords

CLINICAL TRIAL (TOPIC); COMPUTER SIMULATION; HUMAN; LONGITUDINAL STUDY; METHODOLOGY; SAMPLE SIZE; STATISTICAL MODEL;

CLINICAL TRIALS AS TOPIC; COMPUTER SIMULATION; HUMANS; LONGITUDINAL STUDIES; MODELS, STATISTICAL; RESEARCH DESIGN; SAMPLE SIZE;

EID: 84906842457     PISSN: 02776715     EISSN: 10970258     Source Type: Journal    
DOI: 10.1002/sim.6192     Document Type: Article

References (21)

1. Lu K, Luo X, Chen PY. Sample size estimation for repeated measures analysis in randomized clinical trials with missing data. The International Journal of Biostatistics 2008; 4(1):1-16.
2. Lu K, Mehrotra DV, Liu G. Sample size determination for constrained longitudinal data analysis. Statistics in Medicine 2009; 28(4):679-699.
3. Coffey CS, Kairalla JA. Adaptive clinical trials: progress and challenges. Drugs in R&D 2008; 9(4):220-242.
4. Chuang-Stein C, Anderson K, Gallo P, Collins S. Sample size reestimation: a review and recommendations. Drug Information Journal 2006; 40(4):475-484.
5. Wittes J, Brittain E. The role of internal pilot studies in increasing the efficiency of clinical trials. Statistics in Medicine 1990; 9(1-2):65-72.
6. Shih WJ, Gould AL. Re-evaluating design specifications of longitudinal clinical trials without unblinding when the key response is rate of change. Statistics in Medicine 1995; 14(20):2239-2248.
7. Zucker DM, Denne J. Sample-size redetermination for repeated measures studies. Biometrics 2002; 58(3):548-559.
8. Jennison C, Turnbull BW. Group Sequential Methods with Applications to Clinical Trials. CRC Press: Boca Raton, FL, 2000.
9. Galbraith S, Marschner IC. Interim analysis of continuous long-term endpoints in clinical trials with longitudinal outcomes. Statistics in Medicine 2003; 22(11):1787-1805.
10. Kittelson JM, Sharples K, Emerson SS. Group sequential clinical trials for longitudinal data with analyses using summary statistics. Statistics in Medicine 2005; 24(16):2457-2475.
11. Burington BE, Emerson SS. Flexible implementations of group sequential stopping rules using constrained boundaries. Biometrics 2003; 59: 770-777.
12. Mehta CR, Tsiatis AA. Flexible sample size considerations using information-based interim monitoring. Drug Information Journal 2001; 35(4):1095-1112.
13. Tsiatis AA. Information-based monitoring of clinical trials. Statistics in Medicine 2006; 25(19):3236-3244.
14. Liang KY, Zeger SL. Longitudinal data analysis of continuous and discrete responses for pre-post designs. Sankhyā: The Indian Journal of Statistics, Series B 2000; 62: 134-148.
15. Scharfstein DO, Tsiatis AA, Robins JM. Semiparametric efficiency and its implication on the design and analysis of group-sequential studies. Journal of the American Statistical Association 1997; 92(440):1342-1350.
16. Zhu L, Ni L, Yao B. Group sequential methods and software applications. The American Statistician 2011; 65(2):127-135.
17. Diggle P. Analysis of Longitudinal Data, Vol.25. Oxford University Press: USA, 2002.
18. Lan KKG, DeMets DL. Discrete sequential boundaries for clinical trials. Biometrika 1983; 70(3):659-663.
19. Gao P, Liu L, Mehta C. Exact inference for adaptive group sequential designs. Statistics in Medicine 2013; 32(23):3991-4005.
20. Emerson SS, Fleming TR. Parameter estimation following group sequential hypothesis testing. Biometrika 1990; 77(4):875-892.
21. Kim K. Point estimation following group sequential tests. Biometrics 1989; 45(2):613-617.