This example tests a binomial proportion by using a fourstage group sequential design. Suppose a supermarket is developing a new storebrand coffee. From past studies, the positive response for the current storebrand coffee from customers is around . The store is interested in whether the new brand has a better positive response than the current brand.
A power family method is used for the group sequential trial with the null hypothesis and a onesided upper alternative with a power of at . To accommodate the zero null reference that is assumed in the SEQDESIGN procedure, an equivalent hypothesis with is used, where . The following statements request a power family method with early stopping to reject the null hypothesis:
ods graphics on; proc seqdesign altref=0.10 boundaryscale=mle ; PowerFamily: design method=pow nstages=4 alt=upper beta=0.20 ; samplesize model=onesamplefreq( nullprop=0.6); ods output Boundary=Bnd_Prop; run; ods graphics off;
The NULLPROP= option in the SAMPLESIZE statement specifies for the sample size computation. The ODS OUTPUT statement with the BOUNDARY=BND_PROP option creates an output data set named BND_PROP which contains the resulting boundary information for the subsequent sequential tests.
With the BOUNDARYSCALE=MLE option, the procedure displays the output boundaries in terms of the maximum likelihood estimates. The "Design Information" table in Output 81.4.1 displays design specifications and derived statistics. With the specified alternative reference , the maximum information is also derived.
Design Information  

Statistic Distribution  Normal 
Boundary Scale  MLE 
Alternative Hypothesis  Upper 
Early Stop  Reject Null 
Method  Power Family 
Boundary Key  Both 
Alternative Reference  0.1 
Number of Stages  4 
Alpha  0.05 
Beta  0.2 
Power  0.8 
Max Information (Percent of Fixed Sample)  108.4306 
Max Information  670.3782 
Null Ref ASN (Percent of Fixed Sample)  106.9276 
Alt Ref ASN (Percent of Fixed Sample)  78.51072 
The "Boundary Information" table in Output 81.4.2 displays the information level, alternative reference, and boundary values at each stage. With the STOP=REJECT option, only the rejection boundary values are displayed.
Boundary Information (MLE Scale) Null Reference = 0 


_Stage_  Alternative  Boundary Values  
Information Level  Reference  Upper  
Proportion  Actual  N  Upper  Alpha  
1  0.2500  167.5945  35.19485  0.10000  0.20018 
2  0.5000  335.1891  70.38971  0.10000  0.11903 
3  0.7500  502.7836  105.5846  0.10000  0.08782 
4  1.0000  670.3782  140.7794  0.10000  0.07077 
With ODS Graphics enabled, a detailed boundary plot with the rejection and acceptance regions is displayed, as shown in Output 81.4.3.
With the MODEL=ONESAMPLEFREQ option in the SAMPLESIZE statement, the "Sample Size Summary" table in Output 81.4.4 displays the parameters for the sample size computation.
Sample Size Summary  

Test  OneSample Proportion 
Null Proportion  0.6 
Proportion  0.7 
Test Statistic  Z for Proportion 
Reference Proportion  Alt Ref 
Max Sample Size  140.7794 
Expected Sample Size (Null Ref)  138.828 
Expected Sample Size (Alt Ref)  101.9333 
The "Sample Sizes" table in Output 81.4.5 displays the required sample sizes for the group sequential clinical trial.
Sample Sizes (N) OneSample Z Test for Proportion 


_Stage_  Fractional N  Ceiling N  
N  Information  N  Information  
1  35.19  167.6  36  171.4 
2  70.39  335.2  71  338.1 
3  105.58  502.8  106  504.8 
4  140.78  670.4  141  671.4 
Thus, customers are needed at stage , and new customers are needed at each of the remaining stages. Suppose that customers are available at stage . Output 81.4.6 lists the 10 observations in the data set count_1.
First 10 Obs in the Trial Data 
Obs  Resp 

1  1 
2  1 
3  0 
4  0 
5  1 
6  1 
7  0 
8  1 
9  1 
10  1 
The Resp variable is an indicator variable with a value of for a customer with a positive response and a value of for a customer without a positive response.
The following statements use the MEANS procedure to compute the mean response at stage :
proc means data=Prop_1; var Resp; ods output Summary=Data_Prop1; run;
The following statements create and display (in Output 81.4.7) the data set for the centered mean positive response, :
data Data_Prop1; set Data_Prop1; _Scale_='MLE'; _Stage_= 1; NObs= Resp_N; PDiff= Resp_Mean  0.6; keep _Scale_ _Stage_ NObs PDiff; run; proc print data=Data_Prop1; title 'Statistics Computed at Stage 1'; run;
Statistics Computed at Stage 1 
Obs  _Scale_  _Stage_  NObs  PDiff 

1  MLE  1  36  0.016667 
The following statements invoke the SEQTEST procedure to test for early stopping at stage :
ods graphics on; proc seqtest Boundary=Bnd_Prop Data(Testvar=PDiff)=Data_Prop1 infoadj=prop boundarykey=both boundaryscale=mle ; ods output Test=Test_Prop1; run; ods graphics off;
The BOUNDARY= option specifies the input data set that provides the boundary information for the trial at stage , which was generated in the SEQDESIGN procedure. The DATA=DATA_PROP1 option specifies the input data set DATA_PROP1 that contains the test statistic and its associated sample size at stage , and the TESTVAR=PDIFF option identifies the test variable PDIFF in the data set.
If the computed information level for stage is not the same as the value provided in the BOUNDARY= data set, the INFOADJ=PROP option (which is the default) proportionally adjusts the information levels at future interim stages from the levels provided in the BOUNDARY= data set. The BOUNDARYKEY=BOTH option maintains both the and levels. The BOUNDARYSCALE=MLE option displays the output boundaries in terms of the MLE scale.
The ODS OUTPUT statement with the TEST=TEST_PROP1 option creates an output data set named TEST_PROP1 which contains the updated boundary information for the test at stage . The data set also provides the boundary information that is needed for the group sequential test at the next stage.
The "Design Information" table in Output 81.4.8 displays design specifications. With the specified BOUNDARYKEY=BOTH option, the information levels and boundary values at future stages are modified to maintain both the and levels.
Design Information  

BOUNDARY Data Set  WORK.BND_PROP 
Data Set  WORK.DATA_PROP1 
Statistic Distribution  Normal 
Boundary Scale  MLE 
Alternative Hypothesis  Upper 
Early Stop  Reject Null 
Number of Stages  4 
Alpha  0.05 
Beta  0.2 
Power  0.8 
Max Information (Percent of Fixed Sample)  108.4795 
Max Information  670.680662 
Null Ref ASN (Percent of Fixed Sample)  106.9693 
Alt Ref ASN (Percent of Fixed Sample)  78.44835 
The "Test Information" table in Output 81.4.9 displays the boundary values for the test statistic with the specified MLE scale.
Test Information (MLE Scale) Null Reference = 0 


_Stage_  Alternative  Boundary Values  Test  
Information Level  Reference  Upper  PDiff  
Proportion  Actual  N  Upper  Alpha  Estimate  Action  
1  0.2556  171.4286  35.98376  0.10000  0.19638  0.01667  Continue 
2  0.5037  337.8459  70.91565  0.10000  0.11843  .  
3  0.7519  504.2633  105.8475  0.10000  0.08770  .  
4  1.0000  670.6807  140.7794  0.10000  0.07080  . 
The information level at stage is computed as , where and are the information level and sample size at stage in the BOUNDARY= data set, and is the available sample size at stage .
With the INFOADJ=PROP option (which is the default), the information levels at interim stages and are derived proportionally from the information levels in the BOUNDARY= data set. At stage , the statistic is less than the upper boundary value , so the trial continues to the next stage.
With ODS Graphics enabled, a boundary plot with the rejection and acceptance regions is displayed, as shown in Output 81.4.10. As expected, the test statistic is in the continuation region.
The following statements use the MEANS procedure to compute the mean response at stage :
proc means data=Prop_2; var Resp; ods output Summary=Data_Prop2; run;
The following statements create and display (in Output 81.4.11) the data set for the centered mean positive response () at stage :
data Data_Prop2; set Data_Prop2; _Scale_='MLE'; _Stage_= 2; NObs= Resp_N; PDiff= Resp_Mean  0.6; keep _Scale_ _Stage_ NObs PDiff; run; proc print data=Data_Prop2; title 'Statistics Computed at Stage 2'; run;
Statistics Computed at Stage 2 
Obs  _Scale_  _Stage_  NObs  PDiff 

1  MLE  2  71  0.064789 
The following statements invoke the SEQTEST procedure to test for early stopping at stage :
ods graphics on; proc seqtest Boundary=Test_Prop1 Data(Testvar=PDiff)=Data_Prop2 infoadj=prop boundarykey=both boundaryscale=mle condpower(cref=1) predpower plots=condpower ; ods output test=Test_Prop2; run; ods graphics off;
The BOUNDARY= option specifies the input data set that provides the boundary information for the trial at stage , which was generated by the SEQTEST procedure at the previous stage. The DATA= option specifies the input data set that contains the test statistic and its associated sample size at stage , and the TESTVAR= option identifies the test variable in the data set.
The ODS OUTPUT statement with the TEST=TEST_PROP2 option creates an output data set named TEST_PROP2 which contains the updated boundary information for the test at stage . The data set also provides the boundary information that is needed for the group sequential test at the next stage.
The CONDPOWER(CREF=1) option requests the conditional power with the observed statistic under the alternative hypothesis, in addition to the conditional power under the hypothetical reference , the MLE estimate. The PREDPOWER option requests the noninformative predictive power with the observed statistic.
The "Test Information" table in Output 81.4.12 displays the boundary values for the test statistic with the specified MLE scale. The test statistic is less than the corresponding upper boundary , so the sequential test does not stop at stage to reject the null hypothesis.
Test Information (MLE Scale) Null Reference = 0 


_Stage_  Alternative  Boundary Values  Test  
Information Level  Reference  Upper  PDiff  
Proportion  Actual  N  Upper  Alpha  Estimate  Action  
1  0.2556  171.4286  35.98223  0.10000  0.19638  0.01667  Continue 
2  0.5043  338.2478  70.99698  0.10000  0.11831  0.06479  Continue 
3  0.7522  504.4785  105.8882  0.10000  0.08767  .  
4  1.0000  670.7092  140.7794  0.10000  0.07081  . 
With ODS Graphics enabled, the "Test Plot" displays boundary values of the design and the test statistic, as shown in Output 81.4.13. It also shows that the test statistic is in the "Continuation Region" below the upper boundary value at stage .
The predictive power is the probability to reject the null hypothesis under the posterior distribution with a noninformative prior given the observed statistic . The "Predictive Power Information" table in Output 81.4.14 indicates that the predictive power at is .
Predictive Power Information  

Stopping Stage 
MLE  Predictive Power 
2  0.06479  0.00020 
The "Conditional Power Information" table in Output 81.4.15 displays conditional powers given the observed statistic under hypothetical references , the maximum likelihood estimate, and . The constant under CRef for the MLE is derived from ; that is, .
Conditional Power Information Reference = CRef * (Alt Reference) 


Stopping Stage 
MLE  Reference  Conditional Power 

Ref  CRef  
2  0.06479  MLE  0.6479  0.00000 
2  0.06479  Alternative  1.0000  0.02368 
The conditional power is the probability of rejecting the null hypothesis under these hypothetical references given the observed statistic . The table in Output 81.4.15 shows a weak conditional power of under the alternative hypothesis.
The "Conditional Power Plot" displays conditional powers given the observed statistic under various hypothetical references, as shown in Output 81.4.16. These references include , the maximum likelihood estimate, and , where is the alternative reference and are constants that are specified in the CREF= option. Output 81.4.16 shows that the conditional power increases as increases.
With a predictive power and a conditional power of under , the supermarket decides to stop the trial and accept the null hypothesis. That is, the positive response for the new storebrand coffee is not better than that for the current storebrand coffee.
Predictive Power Information  

Stopping Stage 
MLE  Predictive Power 
2  0.06479  0.00020 
In the SEQTEST procedure, the conditional probability at an interim stage is the probability that the test statistic at the final stage (stage ) would exceed the rejection critical value. Since an interim stage exists between the current stage (stage ) and the final stage, the conditional power is not the conditional probability to reject the null hypothesis .
The following statements invoke the SEQTEST procedure to test for early stopping at stage . The NSTAGES=3 option sets the next stage as the final stage (stage ), and the BOUNDARYKEY=BOTH option derives the information level at stage that maintain both Type I and Type II error probability levels. The CONDPOWER(CREF=1) option requests the conditional power with the observed statistic under the alternative hypothesis, in addition to the conditional power under the hypothetical reference , the MLE estimate.
proc seqtest Boundary=Test_Prop1 Data(Testvar=PDiff)=Data_Prop2 nstages=3 boundarykey=both boundaryscale=mle condpower(cref=1) ; run;
The "Test Information" table in Output 81.4.18 displays the boundary values for the test statistic with the specified MLE scale, assuming that the next stage is the final stage.
Test Information (MLE Scale) Null Reference = 0 


_Stage_  Alternative  Boundary Values  Test  
Information Level  Reference  Upper  PDiff  
Proportion  Actual  N  Upper  Alpha  Estimate  Action  
1  0.2645  171.4286  37.23405  0.10000  0.19638  0.01667  Continue 
2  0.5219  338.2478  73.46696  0.10000  0.11831  0.06479  Continue 
3  1.0000  648.1598  140.7794  0.10000  0.06831  . 
The "Conditional Power Information" table in Output 81.4.19 displays conditional powers given the observed statistic, assuming that the next stage is the final stage.
Conditional Power Information Reference = CRef * (Alt Reference) 


Stopping Stage 
MLE  Reference  Conditional Power 

Ref  CRef  
2  0.06479  MLE  0.6479  0.00000 
2  0.06479  Alternative  1.0000  0.02278 
The conditional power is the probability of rejecting the null hypothesis under these hypothetical references given the observed statistic . The table in Output 81.4.19 also shows a weak conditional power of under the alternative hypothesis.