What Can I say about this output for Conditional Logistic Re

 What Can I say about this output for Conditional Logistic Regression for Binary Matched Pairs?    Call: coxph(formula = Surv(rep(1, 2 * 144), MI) ~ diabetes + strata(pair),      data = table8.3, method = \"exact\")    n= 288, number of events= 144              coef exp(coef) se(coef)     z Pr(>|z|)    diabetes 0.8383    2.3125   0.2992 2.802  0.00508 ** --- Signif. codes:  0 

Solution

Since there is one response level, measures of association between the observed and predicted values were not calculated.

In this model the predictor variable is diabetes. The odds ratio estimate for diabetes is 2.312, which is an estimate of the relative risk for diabetes.. The 95% confidence interval for the odds ratio for diabetes is (1.286,4.157) which does not contain unity , the prognostic factor diabetes is statistically significant.