Title "Proc StdRate: Descriptive Analytics about Confounding"; data Alaska; State='Alaska'; input Sex $ Age $ Death PYear comma9. @@; datalines; Male 00-14 37 81,205 Male 15-34 68 93,662 Male 35-54 206 108,615 Male 55-74 369 35,139 Male 75+ 556 5,491 Female 00-14 78 77,203 Female 15-34 181 85,412 Female 35-54 395 100,386 Female 55-74 555 32,118 Female 75+ 479 7,701 ;run; data Florida; State='Florida'; input Sex $ Age $ Death comma8. PYear comma11. @@; datalines; Male 00-14 1,189 1,505,889 Male 15-34 2,962 1,972,157 Male 35-54 10,279 2,197,912 Male 55-74 26,354 1,383,533 Male 75+ 42,443 554,632 Female 00-14 906 1,445,831 Female 15-34 1,234 1,870,430 Female 35-54 5,630 2,246,737 Female 55-74 18,309 1,612,270 Female 75+ 53,489 868,838 ;run; data US; input Sex $ Age $ PYear comma12. @@; datalines; Male 00-14 30,854,207 Male 15-34 40,199,647 Male 35-54 40,945,028 Male 55-74 19,948,630 Male 75+ 6,106,351 Female 00-14 29,399,168 Female 15-34 38,876,268 Female 35-54 41,881,451 Female 55-74 22,717,040 Female 75+ 10,494,416 ;run; data TwoStates; length State $ 7.; set Alaska Florida; run;proc logistic data=TwoStates; class state age sex; model Death/PYear =state/ outroc=rocout lackfit rsq; run;quit; * You will get negative estimate for the state Alaska ; * which is basically the z-test of group means ; * This implies Florida has higher mortality rate; proc logistic data=TwoStates desc; class state age sex; model Death/PYear =sex state age sex*state state*age sex*age state*sex*age/ outroc=rocout lackfit rsq; run;quit; * You will get positive estimate for the state Alaska ; * This implies Florida actually has lower mortality rate; * which one is correct result? ;