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MRB3855
Fluorite | Level 6

Good day All: Suppose I have the data (x_data) below, and further suppose I want to calculate  confidence intervals for the difference of two binomial proportions (treat A vs treat B for each trial, respectively) via proc freq as below:

proc freq data=x_data;
by trial;
tables treat*outcome /riskdiff(cl=(exact));
weight count;
exact riskdiff;
run;

proc freq data=x_data;
by trial;
tables treat*outcome /riskdiff(cl=(exact));
weight count;
exact riskdiff(method=fmscore);
run;

trial       treat     outcome count

1Ax56
1Ay14
1Bx48
1By32
2Ax9
2Ay1
2Bx3
2By7
3Ax10
3Ay0
3Bx0
3By20

I expected to get different results from the two different procedures, but I don't. The confidence intervals are exactly the same. My understanding is the former should use the Santner-Snell method ("By default, PROC FREQ uses the unstandardized risk difference as the test statistic in the confidence limit computations.") and the latter should use the Chan-Zhang method ("If you specify the RISKDIFF(METHOD=FMSCORE) option, the procedure uses the Farrington-Manning score statistic (Chan and Zhang 1999).").

What gives? BTW, I'm currently using SAS 9.4 TS Level 1M5.  

Thanks

 
1 ACCEPTED SOLUTION

Accepted Solutions
MRB3855
Fluorite | Level 6

Ah, I've found the problem (via a careful read of log file). Stat v 14.3 switches the default from previous versions.

From the log file: 

NOTE: The default method for EXACT RISKDIFF is now METHOD=SCORE. To use the previous default
      method (in SAS/STAT 14.2 and earlier releases), you can specify EXACT
      RISKDIFF(METHOD=NOSCORE).

Problem solved!

As you were 😉   

View solution in original post

1 REPLY 1
MRB3855
Fluorite | Level 6

Ah, I've found the problem (via a careful read of log file). Stat v 14.3 switches the default from previous versions.

From the log file: 

NOTE: The default method for EXACT RISKDIFF is now METHOD=SCORE. To use the previous default
      method (in SAS/STAT 14.2 and earlier releases), you can specify EXACT
      RISKDIFF(METHOD=NOSCORE).

Problem solved!

As you were 😉   

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