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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. | == Matched pairs analysis == Suppose we are interested in pairs of siblings, one whose has been treated for cancer (case) and one who has not (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 [http://www2.chass.ncsu.edu/garson/pa765/logit.htm (outlined under the section entitled conditional logit models about two-thirds of the way down the page)] The straightforward generalisation to three or more dichotomous matched responses is also described. |
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||||||||||||<20% style="VERTICAL-ALIGN: top; TEXT-ALIGN: center">Case/Control ||Disorder ||Pair ||Duplicate ||Iq || ||||||||||||<20% style="VERTICAL-ALIGN: top; TEXT-ALIGN: center"> 2 || 0 ||1 || 2 || 23 || ||||||||||||<20% style="VERTICAL-ALIGN: top; TEXT-ALIGN: center"> 1 || 1 ||1 || 1 || 12 || ||||||||||||<20% style="VERTICAL-ALIGN: top; TEXT-ALIGN: center"> 2 || 0 ||2 || 2 || 11 || ||||||||||||<20% style="VERTICAL-ALIGN: top; TEXT-ALIGN: center"> 1 || 1 ||2 || 1 || 39 || ||||||||||||<20% style="VERTICAL-ALIGN: top; TEXT-ALIGN: center"> 2 || 0 ||3 || 2 || 23 || ||||||||||||<20% style="VERTICAL-ALIGN: top; TEXT-ALIGN: center"> 1 || 1 ||3 || 1 || 12 || ||||||||||||<20% style="VERTICAL-ALIGN: top; TEXT-ALIGN: center"> 2 || 0 ||4 || 2 || 63 || ||||||||||||<20% style="VERTICAL-ALIGN: top; TEXT-ALIGN: center"> 1 || 1 ||4 || 1 || 12 || ||||||||||||<20% style="VERTICAL-ALIGN: top; TEXT-ALIGN: center"> 2 || 1 ||5 || 2 || 17 || ||||||||||||<20% style="VERTICAL-ALIGN: top; TEXT-ALIGN: center"> 1 || 0 ||5 || 1 || 34 || ||||||||||||<20% style="VERTICAL-ALIGN: top; TEXT-ALIGN: center"> 2 || 1 ||6 || 2 || 29 || ||||||||||||<20% style="VERTICAL-ALIGN: top; TEXT-ALIGN: center"> 1 || 0 ||6 || 1 || 11 || |
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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). | The disorder term, obtained by taking the reciprocal of the regression estimates, gives the relative risk of 1/0.553 = 1.81 with 95% confidence interval(1/3.192, 1/0.096) = (0.31,10.42). Given one sibling has the psychiatric disorder it is 1.8 times more likely to be the one whose has been treated for cancer. This is not a statistically significant association. (chi-square(1)=0.45, p=0.50). Another example of the above technique (also known as conditional logistic regression) using the syntax above in SPSS is given [http://www.spsstools.net/Syntax/RegressionRepeatedMeasure/ConditionalLogisticRegression.txt here.] The analogous procedure in R is the Clogit procedure. A worked example is illustrated near the end of [http://www-stat.stanford.edu/~owen/courses/306a/Splusdiscrete2.pdf here.] See [:FAQ/clogit: here.] [:FAQ/MatchedPairs/MultiNomial:Alternatively you can use the Multinomial Logistic Regression procedure in SPSS] |
Matched pairs analysis
Suppose we are interested in pairs of siblings, one whose has been treated for cancer (case) and one who has not (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 [http://www2.chass.ncsu.edu/garson/pa765/logit.htm (outlined under the section entitled conditional logit models about two-thirds of the way down the page)] 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 |
|||||
2 |
0 |
4 |
2 |
63 |
|||||
1 |
1 |
4 |
1 |
12 |
|||||
2 |
1 |
5 |
2 |
17 |
|||||
1 |
0 |
5 |
1 |
34 |
|||||
2 |
1 |
6 |
2 |
29 |
|||||
1 |
0 |
6 |
1 |
11 |
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, obtained by taking the reciprocal of the regression estimates, gives the relative risk of 1/0.553 = 1.81 with 95% confidence interval(1/3.192, 1/0.096) = (0.31,10.42). Given one sibling has the psychiatric disorder it is 1.8 times more likely to be the one whose has been treated for cancer. This is not a statistically significant association. (chi-square(1)=0.45, p=0.50).
Another example of the above technique (also known as conditional logistic regression) using the syntax above in SPSS is given [http://www.spsstools.net/Syntax/RegressionRepeatedMeasure/ConditionalLogisticRegression.txt here.] The analogous procedure in R is the Clogit procedure. A worked example is illustrated near the end of [http://www-stat.stanford.edu/~owen/courses/306a/Splusdiscrete2.pdf here.] See [:FAQ/clogit: here.]
[:FAQ/MatchedPairs/MultiNomial:Alternatively you can use the Multinomial Logistic Regression procedure in SPSS]