Sample Size and the Detection of Correlation--A Signal Detection Account: Comment on Kareev (2000) and Juslin and Olsson (2005).

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Abstract
Simulations examined the hypothesis that small samples can provide better grounds for inferring the existence of a population correlation, p, than can large samples. Samples of 5, 7, 10, 15, or 30 data pairs were drawn either from a population with p=0 or from one with p>0. When decision accuracy was assessed independently for each level of the decision criterion, there was a criterion-specific small-sample advantage. For liberal criteria, accuracy was greater for large than for small samples, but for conservative criteria, the opposite result occurred. There was no small-sample advantage when accuracy was measured as the area under a receiver operating characteristic curve or as the posterior probability of a hit. The results show that small-sample advantages can occur, but under limited conditions.

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