Dear all, I am currently having some problems with a minor issue. If anyone could please help me I would be very grateful. I hope I have explained my self in an understandable way, otherwise please let me know. I have calculated Odds ratios using the proc freq procedure for chisq measures. These however are the crude numbers and I need to adjust for age. And I am not sure which statistical measure will be the best suited to do so. I am doing a cross sectional study using register based materials. I am comparing to groups and these groups differ significantly age wise. I have found the following code in SAS examples, were they use Cochran-Mantel-Haenszel statistics to adjust for gender: (copy/paste from Base SAS(R) 9.2 Procedures Guide: Statistical Procedures, Third Edition ) Data Migraine; Input Gender $ Treatment $ Response $ Count @@; datalines; female Active Better 16 female Active Same 11 female Placebo Better 5 female Placebo Same 20 male Active Better 12 male Active Same 16 male Placebo Better 7 male Placebo Same 19 The following PROC FREQ statements create a multiway table stratified by Gender, where Treatment forms the rows and Response forms the columns. The CMH option produces the Cochran-Mantel-Haenszel statistics. For this stratified table, estimates of the common relative risk and the Breslow-Day test for homogeneity of the odds ratios are also displayed. The NOPRINT option suppresses the display of the contingency tables. These statements produce Output 3.7.1 through Output 3.7.3. proc freq data=Migraine; tables Gender*Treatment*Response / cmh; weight Count; title 'Clinical Trial for Treatment of Migraine Headaches'; run; My question is how to adjust for age and not gender using the Cochran-Mantel-Haenszel statistics. Do I need to split up the data into age groups 25-35 years, 35-45 years, 45-55 years and so on? My data set is currently not divided into groups but range for 16 years to 100 years +
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