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 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 question
B. Study design
C. Type of subject
D. All of the above
E. A and B

Q4. Which of the following will help to mitigate confounding?

A. Multiple regression model
B. Randomization
C. Stratification
D. All of the above

Q5. Which of these is part of disease exposure? Choose the best answer.

A. high-fat diet

B. cigarette smoking
C. alcohol consumption
D. A, B, and C

Q6. Hypothesis is likely to be included in what type of research studies?

A. Descriptive
B. Analytic
C. 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. Hospitals
B. Households
C. All of the above
D. Hospitals only

Q8. Which of the models can help us to understand unit odds ratio in a case-control study?

A. Multiple linear regression
B. Linear regression
C. Multiple logistic regression
D. 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 assigned
B. Matched
C. Nonrandom assigned
D. 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 hypothesis
B. 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