The SEQDESIGN Procedure
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Overview
- Getting Started
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Syntax
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Details
Fixed-Sample Clinical Trials One-Sided Fixed-Sample Tests in Clinical Trials Two-Sided Fixed-Sample Tests in Clinical Trials Group Sequential Methods Statistical Assumptions for Group Sequential Designs Boundary Scales Boundary Variables Type I and Type II Errors Unified Family Methods Haybittle-Peto Method Whitehead Methods Error Spending Methods Acceptance (beta) Boundary Boundary Adjustments for Overlapping Lower and Upper beta Boundaries Specified and Derived Parameters Applicable Boundary Keys Sample Size Computation Applicable One-Sample Tests and Sample Size Computation Applicable Two-Sample Tests and Sample Size Computation Applicable Regression Parameter Tests and Sample Size Computation Aspects of Group Sequential Designs Summary of Methods in Group Sequential Designs Table Output ODS Table Names Graphics Output ODS Graphics Acknowledgments
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Examples
Creating Fixed-Sample Designs Creating a One-Sided O’Brien-Fleming Design Creating Two-Sided Pocock and O’Brien-Fleming Designs Generating Graphics Display for Sequential Designs Creating Designs Using Haybittle-Peto Methods Creating Designs with Various Stopping Criteria Creating Whitehead’s Triangular Designs Creating a One-Sided Error Spending Design Creating Designs with Various Number of Stages Creating Two-Sided Error Spending Designs with and without Overlapping Lower and Upper beta Boundaries Creating a Two-Sided Asymmetric Error Spending Design with Early Stopping to Reject H0 Creating a Two-Sided Asymmetric Error Spending Design with Early Stopping to Reject or Accept H0
- References
| Boundary Adjustments for Overlapping Lower and Upper beta Boundaries |
For the fixed boundary shape methods and Whitehead methods, the boundary values for all stages are derived simultaneously for each boundary. For a two-sided design with STOP=ACCEPT or STOP=BOTH, simultaneous derivation might result in overlapping of the lower and upper 
boundaries. That is, at an interim stage 
, the lower boundary value might be greater than its corresponding upper boundary value. In this case, these two boundary values are set to missing and the design does not stop at stage to accept the null hypothesis (Jennison and Turnbull 2000, p. 113).
For the error spending methods, the boundary values are derived sequentially for the stages. For a two-sided design with STOP=ACCEPT or STOP=BOTH, a small spending at an interim stage might result in overlapping of the lower and upper boundaries for the two corresponding one-sided tests. Specifically, this form of overlapping occurs at an interim stage if the upper boundary value derived from the one-sided test for the upper alternative is less than the lower boundary value derived from the one-sided test for the lower alternative (Kittelson and Emerson 1999, pp. 881–882; Rudser and Emerson 2007, p. 6). You can use the BETAOVERLAP= option to specify how this type of overlapping is to be handled.
If BETAOVERLAP=ADJUST (which is the default) is specified, the procedure derives the boundary values for the two-sided design and then checks for overlapping of the two one-sided boundaries at interim stages. If overlapping occurs at a particular stage, the boundary values for the two-sided design are set to missing (so the trial does not stop to accept the null hypothesis at this stage), and the spending values at subsequent stages are adjusted proportionally as follows.
If the boundary values are set to missing at stage in a 
-stage trial, the adjusted spending value at stage , 
, is updated for these missing boundary values, and then the spending values at subsequent stages are adjusted proportionally by
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for 
, where 
and 
are the cumulative spending values st stage 
before and after the adjustment, respectively.
After all these adjusted spending values are computed, the boundary values are then further modified for these adjusted spending values.
If you specify BETAOVERLAP=NOADJUST, no adjustment is made when overlapping of one-sided boundaries occurs. The BETAOVERLAP= option is illustrated in Example 80.10.