Below is information from the Long Island Breast Cancer Study, a population-based case-control study to investigate whether self-reported lifetime residential organochloride pesticide use increases breast cancer among women living on Long Island. (Susan L. Teitelbaum, Marilie D. Gammon, Julie A. Britton, Alfred I. Neugut, Bruce Levin, and Steven D. Stellman (2007). Reported Residential Pesticide Use and Breast Cancer Risk on Long Island, New York. American Journal of Epidemiology, 165:643-651.)

Cases were identified through a 'super-rapid' identification network established to ascertain potentially eligible case women with newly diagnosed breast cancer" from all hospitals in Long Island and three large tertiary care hospitals in New York City. Women were eligible to be controls if they did not have a lifetime history of breast cancer and lived in the two catchment counties between August 1, 1996 and July 31, 1997. Controls were frequency matched to cases at 5-year age intervals.

Information included in the present study was collected through in-person structured questionnaires. Respondents self-reported lifetime exposure history to a vast array of potential chemical hazards that may increase risk for breast cancer. Questions elicited detailed information about the types of pesticides used, the duration and amount of use, the proximity of the respondent to the chemical, personal application of the pesticide (versus family member, etc.), and location of the pesticide use (home, lawn, garden, etc.). Questionnaires were administered by trained interviewers. Overall pesticide use (the sum of lifetime applications of all 15 categories), the two combined groups (lawn and garden and nuisance pest), and each of the 15 individual categories were considered in the analyses. Lifetime applications were categorized based on the control distribution.

1. What potential bias could have been introduced if you found out that those who interviewed cases took 30 minutes longer on average than those who interviewed controls? (2 points)

For the purpose of this example, we are going to assume that the effect measure reported in the study is the "truth". That is, there was no misclassification in the Teitelbaum et al. (2007) study and we will assume that exposure and disease were measured perfectly.

Table 4: Results of Study (Truth)

	Case	Control	Total
Ever used pesticides	1,254	1,231	2,485
Never used pesticides	240	305	545
Total	1,494	1,536	3,030

2a. Compute the appropriate measure of association from this study. Provide an interpretation of this measure of association. (4 points)

Suppose that in the study one common lawn/garden pesticide was left off of the list so the interviewers did not ask about this exposure with either cases or controls. This resulted in 15% of both cases (188) and controls (185) being classified as never having used pesticides when they really had.

2b. Would this be a differential or a non-differential information bias? What impact would this have on our odds ratio calculated in Question 2a? (4 points)