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Summary C797 Practice Questions.docx C797 Practice Questions 1. Multiple linear regression models are best used with a. a dichotomous dependent variable. b. any ratio-level variable. c. a normally distributed ratio-level variable. d. all of the above. 2. T$4.99
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Summary C797 Practice Questions.docx C797 Practice Questions 1. Multiple linear regression models are best used with a. a dichotomous dependent variable. b. any ratio-level variable. c. a normally distributed ratio-level variable. d. all of the above. 2. T
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C797 Practice Q C797 Practice Questions 1. Multiple linear regression models are best used with a. a dichotomous dependent variable. b. any ratio-level variable. c. a normally distributed ratio-level variable. d. all of the above. 2. The unadjusted regression coefficients (bs) in a mul...
c797 practice questionsdocx c797 practice questions 1nbspmultiple linear regression models are best used with anbspa dichotomous dependent variable bnbspany ratio level variable cnb
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C797 Practice Questions
1. Multiple linear regression models are best used with
a. a dichotomous dependent variable.
b. any ratio-level variable.
c. a normally distributed ratio-level variable.
d. all of the above.
2. The unadjusted regression coefficients (bs) in a multiple linear regression model give
information about
a. the strongest predictor of the dependent variable.
b. the change in the dependent variable per unit increase in the independent
variable.
c. the adjusted odds of having the condition represented by the dependent
variable given that the independent variable is present.
d. a and b only.
3. The adjusted regression coefficient in a multiple linear regression contains information
about
a. the strongest predictor of the dependent variable.
b. the change in the dependent variable per unit increase in the independent
variable.
c. the adjusted odds of having the condition represented by the dependent
variable given that the independent variable is present.
d. a and b only.
4. The coefficient of determination in a multiple linear regression contains information
about
a. the strongest predictor of the dependent variable.
b. the change in the dependent variable per unit increase in the independent
variable.
c. the adjusted odds of having the condition represented by the dependent
variable given that the independent variable is present.
d. the amount of variance in the dependent variable explained by the model.
5. Linear regression models describe
a. curvilinear relationships only.
b. linear relationships only.
c. both a and b.
d. none of the above.
6. Dummy variables are used to
a. recode the dependent variable.
b. represent ratio variables in regression models.
, c. represent ordinal variables in regression models.
d. represent nominal variables in regression models.
7. Linear regression allows you to test the significance of the following:
a. The overall model
b. Each regression coefficient
c. The risk ratio comparing those with a characteristic to those without
d. a and b only
8. When the outcome is nominal and dichotomous, which form of regression would be
appropriate?
a. Linear regression
b. Logistic regression
c. Multinomial or polytomous regression
d. All of the above
9. Multivariate regression models, be they linear, logistic, or any other form, allow us to
do which of the following?
a. Simultaneously consider the effects of several independent variables on the
dependent variable of interest
b. Look at the association between two variables of nominal scale
c. Minimize the risk of obtaining spurious results
d. a and c
10. Adding an interaction term to the linear regression model allows us to
a. interpret the adjusted association between each independent variable and
the outcome.
b. assess whether there is significant interaction between the two variables
used to create the interaction term.
c. calculate odds ratios.
d. all of the above.
Choosing the Best Statistical Test
For each of the following scenarios (1 to 10), choose the most appropriate test (a to l).
a. Independent t test
b. Mann-Whitney U-test
c. Paired t test
d. Wilcoxon matched-pairs test
e. Logistic regression
f. McNemar test
g. Linear regression
h. Repeated-measures ANOVA
i. Friedman’s ANOVA by rank
j. Kruskal-Wallis ANOVA
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