At each stage, the data are analyzed with a statistical procedure such as the REG procedure, and a test statistic and its associated information level are computed. The information level is the amount of information available about the unknown parameter. For a maximum likelihood statistic, the information level is the inverse of its variance.
At each stage, you use the SEQTEST procedure to compare the test statistic with its boundary values. At stage 1, the boundary values are derived by using the boundary information tables created by the SEQDESIGN procedure. At each subsequent stage, the boundary values are derived by using the test information tables created by the SEQTEST procedure at the previous stage.
If the observed information level does not match the corresponding information level in the BOUNDARY= data set, the SEQTEST procedure modifies the boundary values to adjust for new information levels at the current and subsequent stages. See the section Boundary Adjustments for Information Levels for a detailed description of these boundary adjustments.
Either you can specify the test statistic and its information level in the DATA= input data set, or you can specify the test statistic and its associated standard error in the PARMS= input data set. With the PARMS= input data set, the information level for the test statistic is computed from its standard error. See the section Input Data Sets for a detailed description of these input data sets.
At the end of a trial, the parameter estimate is computed. The median unbiased estimate, confidence limits, and p-value depend on the specified sample space ordering. A sample space ordering specifies the ordering for test statistics that result in the stopping of a trial. That is, for all the statistics in the rejection region and in acceptance region, the SEQTEST procedure provides three different sample space orderings: the stagewise ordering uses counterclockwise ordering around the continuation region, the LR ordering uses the distance between the observed Z statistic z and its hypothetical value, and the MLE ordering uses the observed maximum likelihood estimate. See the section Available Sample Space Orderings in a Sequential Test for a detailed description of these orderings.