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Explain how the researchers can boost the statistical power of their study without increasing the sample size, describing the underlying mechanism of the alternative approaches and how they apply to this research design.
Case context: A research group is investigating the effects of a new study technique on memory retention. In their pilot study, they used a between-subjects design where one group used the technique and another did not. The results showed a tiny, non-significant difference between the groups. An analysis reveals that the study suffers from low statistical power. The budget is very tight, meaning they cannot recruit any more participants, but they still want to increase the statistical power for their next attempt.
Question: Explain how the researchers can boost the statistical power of their study without increasing the sample size, describing the underlying mechanism of the alternative approaches and how they apply to this research design.
Sample answer: Since the researchers cannot increase their sample size, they must focus on strengthening the relationship between variables. They can achieve this by using a stronger experimental manipulation (e.g., making the study technique training more intensive) or by controlling extraneous variables to reduce data noise. A key way to control extraneous variables and reduce noise in this scenario is to switch from a between-subjects design to a within-subjects design, where the same participants test both conditions.
Key points:
- Focus on strengthening the relationship between variables because sample size cannot be increased.
- Use a stronger experimental manipulation to enhance the effect.
- Control extraneous variables to reduce noise in the data.
- Switch from a between-subjects design to a within-subjects design to reduce noise.
Rubric: The answer should correctly identify that power can be increased by strengthening the relationship when sample size cannot be adjusted. It must explain that this is done by either using a stronger manipulation or controlling extraneous variables to reduce data noise. It should specify switching from a between-subjects to a within-subjects design as a concrete application of this control.
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Research Methods in Psychology - 4th American Edition @ KPU
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