The SEQDESIGN procedure assumes that the data are from a multivariate normal distribution and the sequence of the standardized test statistics have the following canonical joint distribution:

• 

•   ,  

where is the total number of stages and is the information available at stage .

If the data are not from a normal distribution such as binomial distribution, then it is assumed that the test statistic is computed from a large sample such that the statistic has an approximately normal distribution.

In a clinical trial, the sample size required depends on the Type I error probability , reference improvement , power , and variance of the response variable. Given a null hypothesis with an upper alternative hypothesis , the information required for a fixed-sample test is given by

where the parameter depends on the test specified in the clinical trial. For example, if you are comparing two binomial populations , then is the difference between two proportions if the proportion difference statistic is used, and , the log odds ratio for the two proportions if the log odds ratio statistic is used.

If the maximum likelihood estimate from the likelihood function can be derived, then the asymptotic variance for is Var, where is Fisher’s information for .

The resulting statistic corresponds to the MLE scale as specified in the BOUNDARYSCALE=MLE option in the PROC SEQDESIGN statement, corresponds to the standardized scale (BOUNDARYSCALE=STDZ), and corresponds to the score scale (BOUNDARYSCALE=SCORE).

Alternatively, if the score statistic is derived, it can also be used as the test statistic and its asymptotic variance is given by Fisher’s information.

For a group sequential trial, the maximum information is derived in the SEQDESIGN procedure by using the specified , , and . With the maximum information

the sample size required for a specified test statistic in the trial can be evaluated or estimated from the known or estimated variance of the response variable. Note that different designs might produce different maximum information levels for the same hypothesis, and this in turn might require a different number of observations for the trial.

With a specified test statistic, the resulting information levels can be computed and then used to derive the required sample size. These tests include commonly used tests for normal means, binomial proportions, and survival distributions. See the section "Applicable Tests and Sample Size Computation" in "The SEQDESIGN Procedure" for a description of these tests.