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Matched Sample Designs to Reduce Selection Effects – Dr. Don Bergh

Research Methods Education Program (RMEP) 2024-2025 Webcast Lecture Series Matched Sample Designs to Reduce Selection Effects – Dr. Don Bergh

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Question 1 of 6

1. Question
1. Sources of endogeneity include…
- a. Omitted variables
- b. Measurement error
- c. Temporal relations
- d. Selection
- e. All the above
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Question 2 of 6

2. Question
2. Selection bias occurs when…
- a. Systematic differences exist between sample and population
- b. Sample does not accurately represent the population
- c. Both (a) and (b)
- d. Neither (a) nor (b)
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Question 3 of 6

3. Question
3. What is the primary challenge with using analytical solutions to address selection bias?
- a. They focus on bias after data has been collected
- b. They are complicated and time consuming
- c. There are no challenges
- d. Both (a) and (b)
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Question 4 of 6

4. Question
4. True or False: Research designs are a source of bias from sample- and self-selection.
- a. True
- b. False
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Question 5 of 6

5. Question
- a. Reduces post-treatment differences in the outcome variable
- b. Creates a control sample to decrease the effects of sample/treatment assignments
- c. Reduces selection-based endogeneity
- d. All the above
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Question 6 of 6

6. Question
6. Which of the following is not an alternative form of matched sampling?
- a. Propensity score matching
- b. Coarsened exact matching
- c. Random selection
- d. None of these
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By Liliana Gomez|2025-01-31T14:57:59-05:00January 31st, 2025|Comments Off on Matched Sample Designs to Reduce Selection Effects – Dr. Don Bergh

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