HOW MANY SUBJECTS DOES IT TAKE TO DO A REGRESSION-ANALYSIS
HOW MANY SUBJECTS DOES IT TAKE TO DO A REGRESSION-ANALYSIS
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DOI：
10.1207/s15327906mbr2603_7
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发表时间：
1991-01-01
影响因子：
3.8
通讯作者：
GREEN, SB
中科院分区：
文献类型：
--
作者：
GREEN, SB
许多经验法则已被建议用于确定进行多元回归分析所需的最小受试者数量。 这些经验法则进行评估，通过比较他们的结果对那些基于功率分析的多重和偏相关的假设检验。 结果不支持使用简单地指定某个常数（例如，100名受试者）作为受试者的最小数量或受试者数量（N）与预测因子数量（m）的最小比值。 一些经验法则得到了支持，即N大于或等于50 + 8 m的多重相关和N大于或等于104 + m的偏相关。 然而，当m大于或等于7时，多重相关的经验法则产生的N值太大，并且两种经验法则都假设所有研究在标准和预测因子之间具有中等大小的关系。 因此，一个稍微复杂的经验法则是介绍，估计最小样本量的功能，效果大小以及预测的数量。 有人认为，研究人员应该使用的方法来确定样本量，纳入效应量。
Numerous rules-of-thumb have been suggested for determining the minimum number of subjects required to conduct multiple regression analyses. These rules-of-thumb are evaluated by comparing their results against those based on power analyses for tests of hypotheses of multiple and partial correlations. The results did not support the use of rules-of-thumb that simply specify some constant (e.g., 100 subjects) as the minimum number of subjects or a minimum ratio of number of subjects (N) to number of predictors (m). Some support was obtained for a rule-of-thumb that N greater-than-or-equal-to 50 + 8 m for the multiple correlation and N greater-than-or-equal-to 104 + m for the partial correlation. However, the rule-of-thumb for the multiple correlation yields values too large for N when m greater-than-or-equal-to 7, and both rules-of-thumb assume all studies have a medium-size relationship between criterion and predictors. Accordingly, a slightly more complex rule-of-thumb is introduced that estimates minimum sample size as function of effect size as well as the number of predictors. It is argued that researchers should use methods to determine sample size that incorporate effect size.