Example 35.5 Analysis of a 2x2 Contingency Table

This example computes chi-square tests and Fisher’s exact test to compare the probability of coronary heart disease for two types of diet. It also estimates the relative risks and computes exact confidence limits for the odds ratio.

The data set FatComp contains hypothetical data for a case-control study of high fat diet and the risk of coronary heart disease. The data are recorded as cell counts, where the variable Count contains the frequencies for each exposure and response combination. The data set is sorted in descending order by the variables Exposure and Response, so that the first cell of the table contains the frequency of positive exposure and positive response. The FORMAT procedure creates formats to identify the type of exposure and response with character values.

   proc format;
      value ExpFmt 1='High Cholesterol Diet'
                   0='Low Cholesterol Diet';
      value RspFmt 1='Yes'
                   0='No';
   run;

   data FatComp;
      input Exposure Response Count;
      label Response='Heart Disease';
      datalines;
   0 0  6
   0 1  2
   1 0  4
   1 1 11
   ;

   proc sort data=FatComp;
      by descending Exposure descending Response;
   run;

In the following PROC FREQ statements, ORDER=DATA option orders the contingency table values by their order in the input data set. The TABLES statement requests a two-way table of Exposure by Response. The CHISQ option produces several chi-square tests, while the RELRISK option produces relative risk measures. The EXACT statement requests the exact Pearson chi-square test and exact confidence limits for the odds ratio.

   proc freq data=FatComp order=data;
      format Exposure ExpFmt. Response RspFmt.;
      tables Exposure*Response / chisq relrisk;
      exact pchi or;
      weight Count;
      title 'Case-Control Study of High Fat/Cholesterol Diet';
   run;

The contingency table in Output 35.5.1 displays the variable values so that the first table cell contains the frequency for the first cell in the data set (the frequency of positive exposure and positive response).