Question 1 Confounding and Effect Modification (16 points) An epidemiologist was interested checking whether gender is a potential confounder or an effect modifier in a case control study The table below presents the data from this study Use the data to answer the accompanying questions in the table below Males Females Exposed Non Exposed Exposed Non Exposed Disease 9100 900 Disease 900 89100 No Disease 990 8110 No Disease 10 81890 Calculate Odds ratio for males and females separately Is there any evidence of interaction in these data (6 points) Complete the crude table relating disease and exposure (ignoring the potential confounder) Is there evidence of confounding due to gender in this data set (10 points) Exposed Non Exposed Disease No Disease

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Question: Question 1: Confounding and Effect Modification (16 points) An epidemiologist was interested checking whether gender is a potential confounder or an effect modifier in a

Question 1: Confounding and Effect Modification (16 points)

An epidemiologist was interested checking whether gender is a potential confounder or an effect modifier in a case-control study. The table below presents the data from this study. Use the data to answer the accompanying questions in the table below:

Males		Females
	Exposed	Non-Exposed		Exposed	Non-Exposed
Disease	9100	900	Disease	900	89100
No-Disease	990	8110	No-Disease	10	81890

Calculate Odds ratio for males and females separately. Is there any evidence of interaction in these data? (6 points)
Complete the crude table relating disease and exposure (ignoring the potential confounder). Is there evidence of confounding due to gender in this data set? (10 points)

	Exposed	Non-Exposed
Disease
No-Disease

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