Consider a study of n = 40 patients. They all suffered a heart attack and have anger management issues. The dataframe has 3 variables: - ha2 Whether or not a patient had a second heart attack. If ha2 = 1, then the patient had a second heart attack; otherwise, ha2 = O. This is the response variable. 0 treatment Whether or not the patient completed an anger control treatment program. 1 means the program was completed, else is is 0. - anxiety A continuous variable that scores the patient's anxiety level. A higher score denotes higher anxiety. We fit a logistic regression model with R. Here is a summary of the fit. > summary(mod) Call: glm(formula = ha2 ~ treatment + anxiety, binomial(link=logit), data = heart.attack) Coefficients: Estimate Std. Error 2 value Pr(>|z|) (Intercept) -6.38342 2.50468 -2.549 0.01082 * treatment -2.73309 1.00548 -2.718 0.00656 ** anxiety 0.13970 0.04819 2.899 0.00374 ** --- Signif. codes: 0 *** 0.001 ** 0.01 * 0.05.0.1 1 {Dispersion parameter for binomial family taken to be 1) Null deviance: 55.452 on 39 degrees of freedom Residual deviance: 29.753 on 37 degrees of freedom AIC: 35.753 Estimate the probability of suffering a 2nd heart attack for someone with an anxiety of 70 and did not complete the anger management program