There is no default value unless cum.mu0 is specified instead. The parameter mu0 must be a positive number. The test specific expected number of events under the null hypothesis. This number should be increased by one each time that the Analyze.Poisson function is run for a new group of data, when it is part of the same sequential analysis. For example, if there were four prior looks at the data, and this is the fifth one, then "test=5". Should never be the same as another sequential analysis that is run simultaneously on the same computer.Īn integer indicating the number of hypothesis tests performed up to and including the current test. Must be identical for all looks at the data, and it must be the same as the name given by the AnalyzeSetup.Poisson function. Usage Analyze.Poisson(name,test,mu0="n",cum.mu0="n",events,AlphaSpend="n") Before running it by the first time, it is necessary to run the AnalyzeSetUp.Poisson function. Analyze.Poisson is run at each look at the data. It is possible to use either a Wald type rejection boundary, which is flat with respect to the likelihood ratio, or a user defined alpha spending function. Moreover, under the null hypothesis, the expected number of events, mu0, can be different for different observations. Unlike CV.Poisson and CV.G.Poisson, it is not necessary to pre-specify the group sizes before the sequential analysis starts. The function Analyze.Poisson is used for either continuous or group sequential analysis, or for a combination of the two. Function to conduct group sequential analyses for Poisson data without the need to know group sizes a priori.
0 Comments
Leave a Reply. |