08-22-2016 10:41 PM - edited 08-22-2016 11:20 PM
Just a 2 by 2 crosser design with two treatments at each period;
Sequence 1: Period 1 --Treatment A; Period 2--Treatment B;
Sequence 2: Period 1 --Treatment B; Period 2-- Treatment A;
Subject will be randomized to sequence 1 or 2;
Each sequence will have 5 subjects;
The variable we want to analyze is a Response binary variable ( with values 0 (No) or 1 (Yes));
The pupose is to check whether the response between two Treatments are same.
Perperty of this design: Each subject will be assessed two times (each for one treatment).
Result have below two cases:
Treatment A: Response=Yes (10 subjects, i.e. all response to Yes for treatment A); Response=No (0 subjects);
Treatment B: Response=Yes (10 subjects, ie. all response to Yes for Treatment B as well); Response=NO (0 Subjects);
Per the posts I raised earlier, the odds ratio for this case is not defined as the cells under Response=0 for both treatments are 0;
Question: I can't calculate the relative risk under this case, right?
Treatment A: Response=Yes (9 subjects, i.e. 9 response to Yes for treatment A); Response=No (1 subjects);
Treatment B: Response=Yes (9 subjects, ie. 9 response to Yes for Treatment B as well); Response=NO (1 Subjects);
Wired thing came out:
When I use below code with the consideration of each subject as stratum, both the odds ratio and relative risk can't be produced.
proc freq data=dar_s(where=(group=5)); tables drgdsc1a*swaevl2C; run; proc freq data=dar_s (where=(group=5)) order=data; BY Group; table SBJ1N*drgdsc1a*SWAEVL2C /alpha=0.1 cmh noprint; output out=ODDS CMH;/*This table is used to calculate the p-value so as to make a commparison with the value produced from PROC LOGISTIC**/ run;
What is your suggestion? Should I not to consider the dependence?
Only use McNemar Test to assess whether the resposne results to two treatments are consistent and test whether the proportion between two treatment for Response=yes is equal?
Highly appreciated for your help .
08-23-2016 12:36 AM
"Question: I can't calculate the relative risk under this case, right?" You can get that as long as it is 2x2 contingency table. tables drgdsc1a*swaevl2C/relrisk(col=2) ; If it was square table , why not use AGREE ? tables drgdsc1a*swaevl2C/agree ;