Minimum Sample Size Recommendations for Conducting Factor Analyses
Minimum Sample Size Recommendations for Conducting Factor Analyses
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DOI：
10.1207/s15327574ijt0502_4
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发表时间：
2005-01-01
影响因子：
1.7
通讯作者：
Ke, Tian Lu
中科院分区：
文献类型：
--
作者：
Mundfrom, Daniel J.;Shaw, Dale G.;Ke, Tian Lu
在进行因子分析时，关于使用的适当样本量的建议并不缺乏。建议的最小样本量包括变量数的3至20倍，绝对范围为100至1 000以上。在大多数情况下，支持这些建议的经验证据很少。该模拟研究解决了180种不同人群条件下的最小样本量要求，这些人群条件在因素数量、每个因素的变量数量和共同性水平方面各不相同。计算一致性系数，以评估群体溶液与各种群体条件下生成的样品溶液之间的一致性。虽然没有提出绝对最小值，但发现一般来说，最小样本量似乎较小，共同性水平较高;最小样本量似乎较小，变量数与因子数的比率较高;当变量与因子的比率超过6时，最小样本量开始稳定，无论因子数或共同性水平如何。
There is no shortage of recommendations regarding the appropriate sample size to use when conducting a factor analysis. Suggested minimums for sample size include from 3 to 20 times the number of variables and absolute ranges from 100 to over 1,000. For the most part, there is little empirical evidence to support these recommendations. This simulation study addressed minimum sample size requirements for 180 different population conditions that varied in the number of factors, the number of variables per factor, and the level of communality. Congruence coefficients were calculated to assess the agreement between population solutions and sample solutions generated from the various population conditions. Although absolute minimums are not presented, it was found that, in general, minimum sample sizes appear to be smaller for higher levels of communality; minimum sample sizes appear to be smaller for higher ratios of the number of variables to the number of factors; and when the variables-to-factors ratio exceeds 6, the minimum sample size begins to stabilize regardless of the number of factors or the level of communality.