Question

3. A researcher collected data to study the effect of smoking on the risk of a heart attack. The variables were x - a categorical variable with the categories: (1) Present smoker (2) Past smoker (smoked but quit) (3) Non-smoker Y - a binary variable defined by: Y 1 if the person had a heart attack Y-0 if the person didn't have a heart attack Since the X-variables are categorical, the researcher coded the X-variable by two dummy variables: X2 =S 1 if past smoker X1 1 If present smoker 0 otherwise 0 otherwise Since Y is a binary variable, the researcher chose to use a logistic regression model (a) Write the general form of the logistic regression equation with the two X-variables. (b) The researcher ran the logistic regression (PROC LOGISTIC), and the parameter estimates came out to be: bo 2.197, b 1.578, b2 2.117. Estimate the probability of getting a heart attack for each of the categories of getting a heart attack than a present smoker. The researcher therefore wrote in his report: "The regression analysis shows that people who quit smoking have a higher risk of getting (c) If you did Part (b) correctly, then you found that a past smoker has a higher probability of a heart attack than people who presently smoke. Therefore, my conclusion is: People who smoke cigarettes should not quit smoking!!" How would you explain these findings? If not, then what is wrong? Is this conclusion valid?

Answer 1

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