裂区设计中交互作用检验的修正 Brown-Forsythe 程序。
Modified Brown-Forsythe Procedure for Testing Interaction Effects in Split-Plot Designs.
出版信息
Multivariate Behav Res. 2006 Dec 1;41(4):549-78. doi: 10.1207/s15327906mbr4104_6.
The standard univariate and multivariate methods are conventionally used to analyze continuous data from groups by trials repeated measures designs, in spite of being extremely sensitive to departures from the multisample sphericity assumption when group sizes are unequal. However, in the last 10 years several authors have offered alternative solutions to these tests that do not rest on this assumption. In an attempt to improve the precision of the Brown-Forsythe (BF) procedure, a new approximate degrees of freedom (df) approach is presented in this article. Unlike the BF test, the new method not only assures that the df will be always positive but also provides invariant solutions under linear transformations of the data. Monte Carlo methods are used to compare the new solution, in terms of control of Type I error rates, with the modified empirical generalized least squares and BF methods. Our extensive numerical studies show that the modified BF procedure outperformed the other two methods for a wide range of conditions.
传统上，采用标准的单变量和多变量方法分析通过试验重复测量设计的组间连续数据，尽管当组大小时不等时，这些方法对多样本球形度假设的偏离极为敏感。然而，在过去的 10 年中，一些作者提出了这些检验的替代解决方案，这些方案不依赖于这一假设。本文提出了一种新的近似自由度(df)方法，以改进布朗-福塞思（BF）程序的精度。与 BF 检验不同，新方法不仅保证 df 始终为正，而且还在数据的线性变换下提供不变解。蒙特卡罗方法用于比较新解，以控制第一类错误率，方法是修改经验广义最小二乘法和 BF 方法。我们广泛的数值研究表明，在广泛的条件下，修改后的 BF 程序优于其他两种方法。
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