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---+ Proper inference from Simon's two-stage designs by [[TatsukiKoyama][Tatsuki Koyama]], [[HeidiChen][Heidi Chen]] and [[WillGray][Will Gray]] ---+++ Introduction There are many software available for constructing a Simon's design. These software usually give sample sizes and critical values for stages 1 and 2, therefore, hypothesis testing is simple to conduct. Analyzing the data beyond hypothesis testing, however, is not straightforward when a Simon's design is used. When the actual stage 2 sample size is different from the one originally planned, data analysis is more complicated. Many previously published clinical trials do not correctly account for such mid-course changes. We present a [[http://viccbiostat.mc.vanderbilt.edu/simon][software]] that computes a preferable _P_ value, a reasonable estimate and a confidence interval for the response rate. The method is based on "Proper inference from Simon's two-stage designs" by Koyama and Chen (under revision as of January 07). ---+++ Notation ---++++ Response Rate * %$p_0 \, \cdots$% Response rate under the null hypothesis * %$p_1 \, \cdots$% Response rate under the alternative hypothesis ---++++ Stage 1 * %$n_1 \, \cdots$% Planned sample size for stage 1. * %$R_1 \, \cdots$% Critical value for stage 1. Note if there are %$R_1$% or more ''successes'' in stage 1, the trial continues to stage 2. ---++++ Stage 2 (planned) * %$n_2 \, \cdots$% Planned sample size for stage 2. * %$R_t \, \cdots$% Planned critical value at the end of stage 2. Note if there are %$R_t$% or more ''successess'' in stage 1 and 2 combined, the null hyopthesis is rejected. ---++++ Stage 2 (actual) * %$n^*_2 \, \cdots$% Actual sample size for stage 2. ---++++ Data * %$X_1 \, \cdots$% Number of successes in stage 1. * %$X_2 \, \cdots$% Number of successes in stage 2 (out of %$n_2$% or %$n^*_2$%). ---+++ [[http://viccbiostat.mc.vanderbilt.edu/simon][>> Inference from a Simon's Design]]
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Topic revision: r28 - 27 May 2009,
TatsukiKoyama
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