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Pages 58-59:
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Pages 58-59:
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Pages 59-62:
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Page 100:
(zip file with Jack's program phaseIsim.R) |
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Page 100:
(Brad's version of Jack's program; bottom of file has function calls that create Table 3.2, Scenario 1.) |
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Pages 104-105:
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Page 110:
(R code for method for toxicity intervals) |
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(R code for the 2-agent dose escalation method) |
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Page 149:
(standalone desktop program to implement the Phase II predictive probability designs of the sort illustrated in Example 4.2) |
Page 152:
(the "lean" version of the Multc clinical trial software that enables stopping for futility, efficacy, or toxicity with binary data |
Page 152:
(simple R implementation of this same basic approach, e.g., Thall Simon and Estey, 1995) |
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Page 156:
(MD Anderson software package used to implement Algorithm 4.3 in Example 4.4) |
Pages 164-157:
(basic R implementation of the optimal biologic dosing method (Algorithm 4.4) using the FFBS method (Algorithm 4.5) in Example 4.5 |
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(basic R implementation of the Huang et al (2009) method adaptive allocation with survival response, illustrated in Example 4.7) |
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(helpful debugging note for previous code from Dr. John Reynolds of Monash University) |
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Page 180:
(package written by David Rossell for implementing the decision-theoretic screening design of Algorithm 4.9; see bottom of page) |
Page 197:
(R program to compute the exact Type I error of the basic Phase III confirmatory trial, Subsection 5.2.1) |
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Pages 197-198:
(R program to simulate the Type I error and other operating characteristics of the basic Phase III confirmatory trial, Example 5.2) |
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Pages 205-207:
(R program to simulate operating characteristics of the basic confirmatory trial with delayed outcomes, Example 5.4) |
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Pages 214-215:
(R program for calculating the predictive probabilities at the 50- or 75-subject interim analyses for the confirmatory trial with auxiliary variables, Example 5.6) |
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Page 251:
(R [BRugs] program to simulate the power curve for the standard hierarchical model for incorporating historical data, in the case of Example 6.1, testing for a treatment effect in the current trial) |
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Page 251:
(WinBUGS code called by the preceding BRugs program) |
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Pages 251-252:
(R [BRugs] program to simulate the power curve for the standard hierarchical model for incorporating historical data, in the case of Example 6.2, testing whether ``to pool or not to pool'') |
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Pages 251-252:
(WinBUGS code called by the preceding BRugs program) |
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Pages 257-260:
(online software for the design and analysis of clinical trials that incorporate historical controls via commensurate priors, for Gaussian data [Example 6.3] and also survival data assuming a piecewise constant hazard) |
Page 267:
(WinBUGS program to implement the bioequivalence model of Ghosh and Gonen (2008), Subsection 6.2.3) |
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Standard two-sample frequentist clinical trial design tool:
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