Putting It Together: Women, Aspirin, and Heart Attacks In a famous study by the Physicians Health Study Group from Harvard University from the late 1980s, 22,000 healthy male physicians were randomly divided into two groups; half the physicians took aspirin every other day, and the others were given a placebo. Of the physicians in the aspirin group, 104 heart attacks occurred; of the physicians in the placebo group, 189 heart attacks occurred. The results were statistically significant, which led to the advice that males should take an aspirin every other day in the interest of reducing the chance of having a heart attack. Does the same advice apply to women? In a randomized, placebo-controlled study, 39,876 healthy women 45 years of age or older were randomly divided into two groups. The women in group 1 received 100 mg of aspirin every other day; the women in group 2 received a placebo every other day. The women were monitored for 10 years to determine if they experienced a cardiovascular
Source: Paul M. Ridker et al. “A Randomized Trial of Low-Dose Aspirin in the Primary Prevension of Cardiovascular Disease in Woman.” New England Journal of Medicine 352: 1293–1304.
- a. What is the population being studied? What is the sample?
- b. What is the response variable? Is it qualitative or quantitative?
- c. What are the treatments?
- d. What type of experimental design is this?
- e. How does randomization deal with the explanatory variables that were not controlled in the study?
- f. Determine whether the proportion of cardiovascular events in each treatment group is different using a two-sample Z-test for comparing two proportions. Use the α = 0.05 level of significance. What is the test statistic?
- g. Determine whether the proportion of cardiovascular events in each treatment group is different using a chi-square test for homogeneity of proportions. Use the α = 0.05 level of significance. What is the test statistic?
- h. Square the test statistic from part (f) and compare it to the test statistic from part (g). What do you conclude?
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