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, and 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 40.5.1 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).
Output 40.5.1: Contingency Table
Case-Control Study of High Fat/Cholesterol Diet |
|
|
Output 40.5.2 displays the chi-square statistics. Because the expected counts in some of the table cells are small, PROC FREQ gives a warning that the asymptotic chi-square tests might not be appropriate. In this case, the exact tests are appropriate. The alternative hypothesis for this analysis states that coronary heart disease is more likely to be associated with a high fat diet, and therefore a one-sided test is appropriate. Fisher’s exact right-sided test analyzes whether the probability of heart disease in the high fat group exceeds the probability of heart disease in the low fat group; because this p-value is small, the alternative hypothesis is supported.
The odds ratio, displayed in Output 40.5.3, provides an estimate of the relative risk when an event is rare. This estimate indicates that the odds of heart disease is 8.25 times higher in the high fat diet group; however, the wide confidence limits indicate that this estimate has low precision.
Output 40.5.2: Chi-Square Statistics
Statistic | DF | Value | Prob |
---|---|---|---|
Chi-Square | 1 | 4.9597 | 0.0259 |
Likelihood Ratio Chi-Square | 1 | 5.0975 | 0.0240 |
Continuity Adj. Chi-Square | 1 | 3.1879 | 0.0742 |
Mantel-Haenszel Chi-Square | 1 | 4.7441 | 0.0294 |
Phi Coefficient | 0.4644 | ||
Contingency Coefficient | 0.4212 | ||
Cramer's V | 0.4644 | ||
WARNING: 50% of the cells have expected counts less than 5. (Asymptotic) Chi-Square may not be a valid test. |
Output 40.5.3: Relative Risk