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3. general considerations for the analysis of case-control ... - IARC

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ANALYSIS OF GROUPED DATA 153<br />

relative risk <strong>for</strong> <strong>the</strong> highest consumption level may vary with age, but <strong>the</strong> chi-square <strong>of</strong> 10.33 on five<br />

degrees <strong>of</strong> freedom does not quite attain nominal significance at p = 0.05, and considerable doubt exists<br />

as to <strong>the</strong> true significance level because <strong>of</strong> <strong>the</strong> small numbers in some tables. There is no evident trend<br />

in <strong>the</strong> relative risk with increasing age.<br />

Expected values and covariances <strong>for</strong> <strong>the</strong> exposure frequencies <strong>of</strong> <strong>the</strong> <strong>case</strong>s within each stratum, calculated<br />

according to <strong>for</strong>mulae (4.35)-(4.37), are presented in Table 4.6. For example, in <strong>the</strong> second<br />

stratum we have<br />

and<br />

The cumulated vector <strong>of</strong> expected exposures e. and covariance matrix V. are shown at <strong>the</strong> bottom <strong>of</strong> <strong>the</strong><br />

table.<br />

The adjusted global test (4.41) df <strong>the</strong> null hypo<strong>the</strong>sis is calculated from <strong>the</strong> total observed values shown<br />

in Table 4.4 and <strong>the</strong> totals shown at <strong>the</strong> bottom <strong>of</strong> Table 4.6 as<br />

where <strong>the</strong> 3 x 3 matrix is <strong>the</strong> inverse <strong>of</strong> <strong>the</strong> cumulated covariance matrix. To find <strong>the</strong> conservative<br />

approximation to this we compute from (4.42)<br />

(29-81.59)'<br />

In calculating <strong>the</strong> adjusted single degree <strong>of</strong> freedom test <strong>for</strong> trend (4.43), we first find <strong>the</strong> denominator<br />

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