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| ||||||||||||<style="TEXT-ALIGN: center"> ||||||<style="TEXT-ALIGN: center">1-tail ||||||<style="TEXT-ALIGN: center">2-tail || ||||||||||||||<20% style="VERTICAL-ALIGN: top; TEXT-ALIGN: center">Case/Control ||Disorder ||Pair ||Duplicate ||Iq || |
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Suppose we are interested in pairs of siblings, one of with cancer (case) and one without (control). We wish to see if cancer treatment increases the risk of acquiring a psychiatric disorder when corrected for a covariate, iq. Such an analysis is possible in SPSS using the Cox regression procedure as outlined under the section entitled conditional logit models (about two-thirds of the way down the page) at http://www2.chass.ncsu.edu/garson/pa765/logit.htm The straightforward generalisation to three or more dichotomous matched responses is also described.
Below is an illustrative example of the described procedure on the sibling cancer data.
Case/Control |
Disorder |
Pair |
Duplicate |
Iq |
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2 |
0 |
1 |
2 |
23 |
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1 |
1 |
1 |
1 |
12 |
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2 |
0 |
2 |
2 |
11 |
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1 |
1 |
2 |
1 |
39 |
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2 |
0 |
3 |
2 |
23 |
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1 |
1 |
3 |
1 |
12 |
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2 |
0 |
4 |
2 |
63 |
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1 |
1 |
4 |
1 |
12 |
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2 |
1 |
5 |
2 |
17 |
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1 |
0 |
5 |
1 |
34 |
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2 |
1 |
6 |
2 |
29 |
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1 |
0 |
6 |
1 |
11 |
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Running the Cox Model below
COXREG case_con /STATUS=duplic(1) /STRATA=pair /CONTRAST (disorder)=Indicator /METHOD=ENTER iq /METHOD=ENTER disorder /PRINT=CI(95) /CRITERIA=PIN(.05) POUT(.10) ITERATE(20) .
The disorder term in the regression gives the odds 1/0.553 = 1.81 with 95% confidence interval of (1/3.192, 1/0.096) = (0.31,10.42). The cancer treatment increases the odds of having a psychiatric disorder by 1.8 however this is not statistically significant. (chi-square(1)=0.45, p=0.50).