Arnau Jaime, Bendayan Rebecca, Blanca María J, Bono Roser
Universidad de Barcelona.
Psicothema. 2012;24(3):449-54.
This study aimed to evaluate the robustness of the linear mixed model, with the Kenward-Roger correction for degrees of freedom, when implemented in SAS PROC MIXED, using split-plot designs with small sample sizes. A Monte Carlo simulation design involving three groups and four repeated measures was used, assuming an unstructured covariance matrix to generate the data. The study variables were: sphericity, with epsilon values of 0.75 and 0.57; group sizes, equal or unequal; and shape of the distribution. As regards the latter, non-normal distributions were introduced, combining different values of kurtosis in each group. In the case of unbalanced designs, the effect of pairing (positive or negative) the degree of kurtosis with group size was also analysed. The results show that the Kenward-Roger procedure is liberal, particularly for the interaction effect, under certain conditions in which normality is violated. The relationship between the values of kurtosis in the groups and the pairing of kurtosis with group size are found to be relevant variables to take into account when applying this procedure.
本研究旨在评估在SAS PROC MIXED中使用小样本量的裂区设计时,采用肯沃德 - 罗杰自由度校正的线性混合模型的稳健性。使用了一个涉及三组和四次重复测量的蒙特卡罗模拟设计,假设采用非结构化协方差矩阵来生成数据。研究变量包括:球形度,其艾普西隆值分别为0.75和0.57;组大小,相等或不相等;以及分布形状。关于后者,引入了非正态分布,在每组中组合了不同的峰度值。在不平衡设计的情况下,还分析了峰度程度与组大小配对(正或负)的影响。结果表明,在某些违反正态性的条件下,肯沃德 - 罗杰方法是宽松的,特别是对于交互效应。发现组内峰度值以及峰度与组大小的配对之间的关系是应用此方法时需要考虑的相关变量。