Although researchers do their best to reduce error within every study, there will always be error. It is important to identify and report any possible error within the research study in order to accurately interpret the research study’s findings. In epidemiologic research, the focus is on assessing confounding and effect modification along with normal statistical measures (p-values, confidence intervals, etc.).
For this Application Assignment, you will calculate and interpret the effects of confounding, random error, and effect modification within epidemiologic research. Read each of the following questions and answer them appropriately:
Design the appropriate 2×2 table, calculate and interpret the appropriate measure of association.
You suspect that the association between alcohol use and CHD might be confounded by smoking. You collect the following data:
Smokers |
Non-Smokers |
|||
CHD |
No CHD |
CHD |
No CHD |
|
Alcohol Use |
80 |
40 |
10 |
20 |
No Alcohol Use |
20 |
10 |
40 |
80 |
Calculate the appropriate measure of association between alcohol use and CHD in both smokers and non-smokers. Discuss whether smoking was a confounder of the association. What is the relationship of alcohol use to CHD after controlling for confounding?
Calculate and interpret the appropriate measure of association between driver’s education and accidents.
The question arose as to whether gender might be an effect modifier of this association. When gender was assessed, the data looked like the following:
Women |
Men |
|||
Accident |
No Accident |
Accident |
No Accident |
|
Driver’s Ed |
10 |
50 |
60 |
120 |
No Driver’s Ed |
40 |
50 |
40 |
80 |
Perform the appropriate calculations to test for effect modification. Interpret your results.