Q1. R2 is the modified version of R that has been adjusted for the number of predictors in the multiple regression model. A. True B. False C. None of the above Q2. Which of these three factors shoul

Q1. R2 is the modified version of R that has been adjusted for the number of predictors in the multiple regression model. A. True B. False C. None of the above Q2. Which of these three factors shoul
Q1. R2 is the modified version of R that has been adjusted for the number of predictors in the multiple regression model. A. TrueB. FalseC. None of the above Q2. Which of these three factors should not be met (i.e., not necessary) for an exposure to qualify as a risk factor? A. There is a dose-response relationship B. Temporality of the exposure and disease are not necessary C. The observed relationship between exposure and the disease is not due to some source of error in the design. D. All of the above Q3. The particular method of analysis to be used in a given study would depend on: A. Research questionB. Study designC. Type of subjectD. All of the aboveE. A and B Q4. Which of the following will help to mitigate confounding? A. Multiple regression modelB. RandomizationC. StratificationD. All of the above Q5. Which of these is part of disease exposure? Choose the best answer. A. high-fat diet B. cigarette smokingC. alcohol consumptionD. A, B, and C Q6. Hypothesis is likely to be included in what type of research studies? A. DescriptiveB. AnalyticC. All of the above D. None of the above Q7. Which of these can serve as the unit of observation in an ecological study? A. HospitalsB. HouseholdsC. All of the aboveD. Hospitals only Q8. Which of the models can help us to understand unit odds ratio in a case-control study? A. Multiple linear regressionB. Linear regressionC. Multiple logistic regressionD. Linear logistic regression Q9. Descriptive research goal is intended to: A. Not test a hypothesis, but to describe the health phenomenon in terms of person, place and time. B. Help determine factors that are associated with or related to morbidity and mortality. C. Determine the causes of morbidity and mortality. D. None of the above Q10. In a natural experiment, the inclusion of an individual in a particular group is typically: A. Randomly assignedB. MatchedC. Nonrandom assignedD. B and C. Q11. Assuming you are a member of a research team convened to study the potential risk factors for an extremely rare blood disorder among the adult population of New York City. a) What study design would be most appropriate for this research? b) Justify the choice of design. Q12. With a good example, explain in your own words the major difference(s) between confounding and effect modification. Q13. You are interested in a study designed to asses the effect of age on systolic blood pressure. a) Clearly state the research question, including both the null and the alternative hypotheses for this study. b) What are the exposure and the outcome variables involved? c) Identify two potentially meaningful confounding variable you would include in this study, and why. c) What is the most relevant statistical analysis you would use and why. 14. You want to compare mean body weight of men ages 20 to 40 in 1970 with men who are 20 to 40 years today. Which is the most appropriate statistics would you use and why? Q15. You are required to examine an association between gender and systolic blood pressure. A. State an appropriate research question, including both the null and the alternative hypothesisB. Identify the dependent and the independent variables.C. State the most appropriate statistics you will use to test the hypothesis and why? Q16. Let’s assume you conducted a statistical analysis designed to examine the association between race and education in a small community in New York City. Using the output below: a. Examine the association between education by race. b. State whether or not the differences are statistically significant, and justify your answer. c. Draw your conclusion regarding the relationship between race and education. race × education2 education2 Total less than 12th grade 12th grade or more race white Count 1126 288 1414 Row % 79.6% 20.4% 100.0% black/other Count 195 20 215 Row % 90.7% 9.3% 100.0% Total Count 1321 308 1629 Row % 81.1% 18.9% 100.0% Chi-Square Tests Value df Asymptotic Sig. (2-tailed) Exact Sig. (2-tailed) Exact Sig. (1-tailed) Pearson Chi-Square 14.90 .⁠000 Likelihood Ratio 17.21 .⁠000 Fisher’s Exact Test .⁠000 .⁠000 Continuity Correction 14.19 .⁠000 Linear-by-Linear Association 14.89 .⁠000 N of Valid Cases 1629