1 University of Southern Queensland, Ipswich, Queensland, Australia.
2 USQ Centre for Psychological Assessment, Springfield Central, Queensland, Australia.
Assessment. 2018 Sep;25(6):793-800. doi: 10.1177/1073191116669784. Epub 2016 Sep 21.
Sample sizes of 50 have been cited as sufficient to obtain stable means and standard deviations in normative test data. The influence of skewness on this minimum number, however, has not been evaluated. Normative test data with varying levels of skewness were compiled for 12 measures from 7 tests collected as part of ongoing normative studies in Brisbane, Australia. Means and standard deviations were computed from sample sizes of 10 to 100 drawn with replacement from larger samples of 272 to 973 cases. The minimum sample size was determined by the number at which both mean and standard deviation estimates remained within the 90% confidence intervals surrounding the population estimates. Sample sizes of greater than 85 were found to generate stable means and standard deviations regardless of the level of skewness, with smaller samples required in skewed distributions. A formula was derived to compute recommended sample size at differing levels of skewness.
已有研究指出，在获得正态测试数据的稳定均值和标准差时，样本量为 50 已足够。然而，目前尚未评估偏度对这一最小样本量的影响。本研究针对澳大利亚布里斯班正在进行的常规研究中的 7 项测试中的 12 项指标，收集了不同偏度水平的常规测试数据。从较大的 272 到 973 例样本中，采用有放回的抽样方法，每次抽取 10 到 100 个样本，计算均值和标准差。最小样本量由均值和标准差估计值均处于围绕总体估计值的 90%置信区间内的样本数量决定。无论偏度水平如何，只要样本量大于 85，就可以得到稳定的均值和标准差，而在偏度分布中则需要更小的样本量。本文还推导出了一个可以计算不同偏度水平下建议样本量的公式。
