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# Problem Set Assignment: Module 5 QUESTION 1 Name four types of information bias. Name at least one way in which each type of bias can be prevented or minimized. QUESTION 2 A cohort study was undertaken to examine the association between high lipid level and coronary heart disease (CHD). Participants were classified as having either a high lipid level (exposed) or a low or normal lipid level (unexposed). Because age is associated with both lipid level and risk of heart disease, age was considered a potential confounder or effect modifier and the age of each subject was recorded. The following data describes the study participants: Overall, there were 11,000 young participants and 9,000 old participants. Of the 4,000 young participants with high lipid levels, 20 of them developed CHD. Of the 6,000 old participants with high lipid levels, 200 of them developed CHD. In the unexposed, 18 young and 65 old participants developed CHD. • Construct the appropriate two by two tables using the data given above. Be sure to label the cells and margins. • Calculate the appropriate crude ratio measure of association combining the data for young and old individuals. • Now, perform a stratified analysis and calculate the appropriate stratum-specific ratio measures of association. What are they? Do the data provide evidence of effect measure modification on the ratio scale? Justify your answer. QUESTION 3 The association between cellular telephone use and the risk of brain cancer was investigated in a case-control study. The study included 475 cases and 400 controls and the following results were seen: Cases Controls Cellular Phone User Yes 270 200 No 205 200 Total 475 400 • Calculate the odds ratio based on these data. • The p value for this odds ratio is 0.06. State your interpretation of this p-value. Gender was considered a potential confounder and effect measure modifier in this study. The data were stratified into males and females in order to assess these issues. Males Females Cases Controls Cases Controls Cellular Phone User Yes 242 150 Yes 28 50 No 100 50 No 105 150 • Calculate the stratum-specific odds ratios. • Is gender a confounder in this study? Briefly justify your answer. Is gender an effect measure modifier in this study? Briefly justify your answer.

Problem Set Assignment: Module 5

QUESTION 1

Name four types of information bias. Name at least one way in which each type of bias can be prevented or minimized.

QUESTION 2

• A cohort study was undertaken to examine the association between high lipid level and coronary heart disease (CHD). Participants were classified as having either a high lipid level (exposed) or a low or normal lipid level (unexposed). Because age is associated with both lipid level and risk of heart disease, age was considered a potential confounder or effect modifier and the age of each subject was recorded. The following data describes the study participants: Overall, there were 11,000 young participants and 9,000 old participants. Of the 4,000 young participants with high lipid levels, 20 of them developed CHD. Of the 6,000 old participants with high lipid levels, 200 of them developed CHD. In the unexposed, 18 young and 65 old participants developed CHD.
• Construct the appropriate two by two tables using the data given above. Be sure to label the cells and margins.
• Calculate the appropriate crude ratio measure of association combining the data for young and old individuals.
• Now, perform a stratified analysis and calculate the appropriate stratum-specific ratio measures of association. What are they?

Do the data provide evidence of effect measure modification on the ratio scale? Justify your answer.

QUESTION 3

• The association between cellular telephone use and the risk of brain cancer was investigated in a case-control study. The study included 475 cases and 400 controls and the following results were seen:
 Cases Controls Cellular Phone User Yes 270 200 No 205 200 Total 475 400
• Calculate the odds ratio based on these data.
• The p value for this odds ratio is 0.06. State your interpretation of this p-value.
• Gender was considered a potential confounder and effect measure modifier in this study. The data were stratified into males and females in order to assess these issues.

 Males Females Cases Controls Cases Controls Cellular Phone User Yes 242 150 Yes 28 50 No 100 50 No 105 150
• Calculate the stratum-specific odds ratios.
• Is gender a confounder in this study?  Briefly justify your answer.

Is gender an effect measure modifier in this study? Briefly justify your answer.

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