Abstract:
The Simon two stage design is a single arm study with an interim analysis. The main purpose of this design is to investigate whether an intervention works or not and to stop the study early for futility. Under the null hypothesis the probability of a success is p0, this is usually taken as the probability of success for the current standard treatment. The probability of a success in this study, p, is tested using the null hypothesis H0:p=p0 versus the alternative hypothesis H1:p>=p1. The probability of success for the alternative hypothesis is fixed to be a pre-specified value p1, where p1>p0. The Simon two stage design consists of studying n1 participants in a first stage and the study stops if there are r1 or fewer responders to the intervention. If there are more than r1 responders in the first stage then the study continues until n participants in total are studied. Then the null hypothesis is not rejected if there are r or fewer responders. Each design must satisfy the type 1 (alpha) and type 2 (beta) errors. The probability of not rejecting H0 can be calculated conditional on any p and let this function be R(p). The design must therefore satisfy the constraints R(p0)>=1-alpha and R(p1)<=beta. The minimax design is one that satisfies these constraints with the smallest total sample size n and the smallest expected sample size under H0. The alternative is to find the "optimal" design which is the design with the smallest expected sample size conditional on the true proportion being specified by the optp() option. The default is optimising the design under the null proportion p0 and this is the classical Simon two stage design, however this command allows greater flexibility.
Language: Stata Requires: Stata version 11 Keywords:Simon's two stage design; optimal design; minimax; single-arm trial (search for similar items in EconPapers) Date: 2009-09-30, Revised 2009-11-18 Note: This module may be installed from within Stata by typing "ssc install simon2stage". Windows users should not attempt to download these files with a web browser.
More software in Statistical Software Components from Boston College Department of Economics Address: Boston College, 140 Commonwealth Avenue, Chestnut Hill MA 02467 USA Contact information at EDIRC. Series data maintained by Christopher F Baum ().
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