The researchers wrote: “On the basis of a pilot test indicating a Cohen’s d of 0.175, we set a target sample size of 1,000 participants, yielding 75% power to detect a small effect size after allowing for 100 exclusions (10%)” (Catapano et al., 2019, p. 426). A “pilot test” is an initial, smaller study usually conducted to gather information to guide the actual, larger study. By “exclusions,” the researchers meant participant data that they didn’t use for some reason—for example, because the participant failed to answer all of the questions. The findings from the pilot test, or initial study, had a Cohen’s d of 0.175, a small effect size. Why is this information useful for planning the sample size for the main study?

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The researchers wrote: “On the basis of a pilot test indicating a Cohen’s d of 0.175, we set a target sample size of 1,000 participants, yielding 75% power to detect a small effect size after allowing for 100 exclusions (10%)” (Catapano et al., 2019, p. 426). A “pilot test” is an initial, smaller study usually conducted to gather information to guide the actual, larger study. By “exclusions,” the researchers meant participant data that they didn’t use for some reason—for example, because the participant failed to answer all of the questions.

The findings from the pilot test, or initial study, had a Cohen’s d of 0.175, a small effect size. Why is this information useful for planning the sample size for the main study?
 
 
A.Researchers now know that there is likely to be only a small effect, so it’s not worth conducting the study after all.
 
 
B.Researchers need to estimate the size of the effect they hope to detect so as to determine how many participants will be necessary to achieve a certain level of statistical power.
 
 
C.The small effect size estimate means that the researchers must aim for even higher statistical power.
 
 
D.Researchers need to estimate the size of the effect they hope to detect so as to estimate how many participants they will likely have to exclude.
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