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Example question 1 A study is conducted to learn about the relation between regular fish consumption (>2 times a week) and colon polyps. In a group of 500 regular fish consumers, there were 6 cases with colon polyps. There were 15 cases with colon polyps in 650 people that did not consume fish regularly. What is the proper effect measure of polyp risk as associated with fish consumtion and how do you calculate it? a. the odds ratio = 6/15 = 0.4; b. the prevalence ratio = 6/15 = 0.4; c. the odds ratio = (6/500)/(15/650) = 0.52; d. the prevalence ratio = (6/500)/(15/650) = 0.52. Example question 2 The authors conducted a study in the state of Iowa to determine whether increased consumption of nitrate from drinking water and other sources was associated with pancreatic cancer. After exclusions for insufficient data, 189 cases of pancreatic cancer were compared to 1,244 non-cases. No association was observed between pancreatic cancer and increasing levels of nitrates in community water supplies (American Journal of Epidemiology, 2004; 159:693 - 701). What was the design of the study? a. Case-control study b. Cross-sectional study c. Parallel intervention study d. Prospective cohort study Example question 3 Suppose that 93 children are selected at random from the general population. Their C-reactive protein (mmol/L) are evaluated. The mean C-reactive protein was 3.2 mmol/L with standard deviation 6.9 mmol/l. The 95% confidence interval for C-reactive protein in the population is therefore calculated as a. 3.2 1.96 b. 3.2 1.96 6.9 93 6.9 2 93 c. 3.2 1.96 6.9 d. None of these answers. Example question 4 Which of the following statements is true? I. Non-parametric tests and log-transformations can be used for non-normally distributed variables. II. Three ways of visual inspection of whether a variable is Normally distributed are the histogram, the scatterplot and the Q-Q-plot a. b. c. d. I is true, II is false; I is false II is true; I and II are true; I and II are false. Output Researchers wanted to compare BMI at baseline between subjects involved in an intensive 6-week weight reduction programme with subjects that participated in a one-day course on healthy eating. These were the results from their SPSS analysis: Group Statistics BMI diet 6-week programma N One-day course Mean Std. Deviation Std. Error Mean 20 34.3830 2.25188 .50353 21 36.2806 1.34923 .29443 Independent Samples Test Levene's Test for Equality of Variances F BMI Equal variances assumed Equal variances not assumed 7.473 Sig. .009 t-test for Equality of Means t df Sig. (2tailed) Mean Differenc e 95% Confidence Interval of the Difference Std. Error Difference Lower Upper -3.292 39 .002 -1.89762 .57645 -3.06360 -.73164 -3.253 30.793 .003 -1.89762 .58330 -3.08758 -.70766 Example question 5 What is the result of the statistical comparison? a. The p-value for the difference between the two groups is p=0.009; b. The p-value for the difference between the two groups is p=0.002; c. The p-value for the difference between the two groups is p=0.003; d. The p-value for the difference between the two groups is p=0.504. Example question 6 What conclusion can you draw from this SPSS output? a. Subjects in the intensive programme have a 1.90 kg/m2 significantly lower BMI at baseline compared to subjects in the one-day course, with a 95% confidence interval of -3.06 to -0.73; b. Subjects in the intensive programme have a 1.90 kg/m2 significantly lower BMI at baseline compared to subjects in the one-day course, with a 95% confidence interval of -3.09 to -0.71; c. Subjects in the intensive programme have a 1.90 kg/m2 non-significantly lower BMI at baseline compared to subjects in the one-day course, with a 95% confidence interval of -3.06 to -0.73; d. Subjects in the intensive programme have a 1.90 kg/m2 non-significantly lower BMI at baseline compared to subjects in the one-day course, with a 95% confidence interval of -3.09 to -0.71.