Analyze how the required sample size per group changes when a researcher decides to increase the statistical power of an independent-samples -test (assuming a large population effect) from to . What does this comparison reveal about the relationship between sample size increases and statistical power gains?
Question: Analyze how the required sample size per group changes when a researcher decides to increase the statistical power of an independent-samples -test (assuming a large population effect) from to . What does this comparison reveal about the relationship between sample size increases and statistical power gains?
Sample answer: To increase power from to , the required sample size per group increases from approximately to participants. This reveals that the relationship is non-linear and highly demanding: to achieve a relatively small gain in power (), the researcher must more than double their sample size, indicating that achieving near-certainty in power requires disproportionately larger investments in sample size.
Key points:
- Specifies the change in sample size from approximately to participants per sample.
- Analyzes that the sample size must more than double to achieve the increase in statistical power.
- Concludes that the relationship is non-linear, with higher levels of power requiring disproportionately larger increases in sample size.
Rubric: Assess if the student identifies the shift from to participants per group, notes that this represents more than a doubling of the sample size, and analyzes the non-linear relationship where higher levels of statistical power require disproportionately more participants.
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Research Methods in Psychology - 4th American Edition @ KPU
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