Frequentist test in Bayesian two-stage designs applied in experimental trials
Abstract
Prediction provides discipline and pragmatic importance to empirical research. The design with the predictive probability approach provides an excellent alternative for conducting multi-stage phase II trials; it is efficient and flexible and possesses desirable statistical properties. . In this paper we consider the Bayesian predictive procedures within the experimental design, for this, we define indices of satisfaction related to a test as a decreasing function of the p-value and satisfaction is higher than the null hypothesis is rejected wider. This design possesses good frequentist properties and allows early termination of the trial. We treated our applications by simulation and real data in experimental planning and sequential designs with binary outcomes.
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References
Guosheng Yin, Nan Chen, J. Jack Lee , Phase II trial design with Bayesian adaptive randomization and predictive probability ,Appl. Statist. (2012) 61, Part 2, pp. 219-235. https://doi.org/10.1111/j.1467-9876.2011.01006.x
Lisa V. Hampson, Christopher Jennison, Group sequential tests for delayed responses, J. R. Statist. Soc. B (2013) 75, Part 1, pp. 3-54.. J. Differential Equations 7, 554-589, (1970). https://doi.org/10.1111/j.1467-9868.2012.01030.x
E. W. Steyerberg, Clinical Prediction Models A Practical Approach to Development, Validation, and Updating, XXVIII, (2009) ,500p, Hardcover.
Lecoutre, G. Derzko, J. M. Grouin. Bayesian predictive approach for inference about proportions, Statistics in Medicine, (1995)14, pp. 1057-1063. https://doi.org/10.1002/sim.4780140924
H. Merabet, Index and prevision of satisfaction in exponential models for clinical trials, Statistica, anno LXIV, n.3, (2004), 441-453.
S. M Berry, B. P. Carlin, J. J Lee, P. Muller, Bayesian Adaptive Methods for Clinical Trials, Chapman & Hall/CRC biostatistics series. , (2011). https://doi.org/10.1201/EBK1439825488
G. Koop, D. J. Poirier, and J. L. Tobias, Bayesian Econometric Methods,(2007). https://doi.org/10.1017/CBO9780511802447
C. M. C. Shein Chung, Adaptive design methods in clinical trials, Chapman & Hall/CRC, (2011).
Luke Akongo Orawo. J. Andres Christen, Bayesian sequential analysis for multiple-arm clinical trials, Stat Comput (2009) 19: 99-109. https://doi.org/10.1007/s11222-008-9074-y
N. A Azadi, P. Fearnhead, G Ridall and J. H. Blok, Bayesian Sequential Experimental Design forn Binary Response Data with Application to Electromyographic Experiments, Bayesian Analysis (2014), 9 , Number 2, pp. 287-306. https://doi.org/10.1214/13-BA855
N. Stallard, Tim Friede, A group-sequential design for clinical trials with treatment selection, Statist. Med. (2008); 27:6209-622. https://doi.org/10.1002/sim.3436
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