Nonproportional Sampling and the Amplification of Correlations
理论分析表明，当两个二元变量在样本中的频率分布比总体更平坦时，样本相关性会被夸大。实验发现人们偏好抽取两类观测数大致相等的样本，导致对相关性的估计偏高。
A theoretical analysis shows that sample correlations between two binary variables will be inflated when the frequency distributions of the two variables are flatter (i.e., closer to equal frequencies for the two values) in the sample than in the population. A correlation-assessment study in which participants were free to choose their own sample revealed an overwhelming preference for samples that included roughly the same number of observations for the two values of dichotomous variables, irrespective of their actual distribution in the population. Subjective estimates of observed correlations followed the sample correlations--which were inflated, as predicted--more closely than the true correlations. People's sampling behavior thus resembles that of a research designer who maximizes the chance of detecting a relationship, at the cost of diminished accuracy in estimating its strength.