S tatistik fo r M P H : 5 F ra d en 4 . u g es statistik u n d erv isn in g : F ...
S tatistik fo r M P H : 5 F ra d en 4 . u g es statistik u n d erv isn in g : F ...
S tatistik fo r M P H : 5 F ra d en 4 . u g es statistik u n d erv isn in g : F ...
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95% confid<strong>en</strong>ce limits <strong>fo</strong>r common <strong>ra</strong>te <strong>ra</strong>tio:1) Calculate ln(RR MH ) = ln(1.45) = 0.3732) Calculate L 1 = ln(RR MH ) − 1.96 · SDand L 2 = ln(RR MH ) + 1.96 · SDHere: SD = |ln(RR √ MH)|= √ 0.373X2MH72.59= 0.044.That is: L 1 = 0.373 − 1.96 · 0.044 = 0.287,L 2 = 0.373 + 1.96 · 0.044 = 0.459.3)The d<strong>es</strong>ired 95% confid<strong>en</strong>ce limits are from exp(L 1 ) = 1.33 toexp(L 2 ) = 1.58.Note: alternative (and more complicated) <strong>fo</strong>rmula <strong>fo</strong>r SD <strong>in</strong> Silva,p.330.25Example:British Doctors cohort study, compar<strong>in</strong>g coronary deaths amongsmokers and non-smokers adjusted <strong>fo</strong>r age (McNeil, 1996)DeathsPerson-yearsAge Group SM Non-SM SM Non-SM RR35-44 32 2 52407 18790 5.7445-54 104 12 43248 10673 2.1455-64 206 28 28612 5710 1.4765-74 186 28 12663 2585 1.3675-84 102 31 5317 1462 0.90Total 630 101 142247 39220 1.72Crude RR = 630/142247101/39220 = 1.72Age-adjustm<strong>en</strong>t not obvious, RR vari<strong>es</strong> among st<strong>ra</strong>ta:Effect-modification/<strong>in</strong>te<strong>ra</strong>ction !?26
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