VALIDITY AND POWER OF TESTS WHEN GROUPS HAVE BEEN BALANCED FOR PROGNOSTIC FACTORS
VALIDITY AND POWER OF TESTS WHEN GROUPS HAVE BEEN BALANCED FOR PROGNOSTIC FACTORS
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DOI：
10.1016/0167-9473(87)90015-6
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发表时间：
1987-08-01
影响因子：
1.8
通讯作者：
FORSYTHE, AB
中科院分区：
文献类型：
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作者：
FORSYTHE, AB
使用计算机模拟实验的显着性水平和功率的方差分析和协方差技术进行了比较。我们考虑通过随机化或“最小化”将病例分组，这是一种旨在防止基线预后变量不平衡的技术。结果表明，除非使用协方差分析进行显著性检验，否则最小化技术可能产生无效检验。当治疗平均值差异不大时，最小化方差分析的效力低于随机化方差分析。当使用协方差分析时，最小化和随机化都将提供可接受的显著性检验，并且比方差分析更有效。此外，最小化的协方差分析比随机化的协方差分析更有效。建议仅当最小化中使用的所有变量也用作协变量时，才应考虑最小化用于组分配。
The significance level and power of analysis of variance and covariance techniques are compared using a computer-simulated experiment. We consider cases assigned to groups by randomization or ‘minimization’, a technique designed to prevent chance imbalance of baseline prognostic variables. The results show that unless analysis of covariance is used for significance testing, the minimization technique can yield invalid tests. Analysis of variance is less powerful with minimization than with randomization when the treatment means are not very different. When analysis of covariance is used, both minimization and randomization will provide an acceptable test of significance, and are more powerful than analysis of variance. In addition, the analysis of covariance, is slightly more powerful with minimization than with randomization. It is suggested that minimization should be considered for group assignmentonlyif all variables used in minimization are also to be used as covariate.