New heterogeneous test statistics for the unbalanced fixed-effect nested design

作者：Guo Jiin Huarng; Billard L; Luh Wei Ming^*

来源：British Journal of Mathematical and Statistical Psychology, 2011, 64(2): 259-276.

DOI：10.1348/000711010X512688

When the underlying variances are unknown or/and unequal, using the conventional F test is problematic in the two-factor hierarchical data structure. Prompted by the approximate test statistics (Welch and Alexander-Govern methods), the authors develop four new heterogeneous test statistics to test factor A and factor B nested within A for the unbalanced fixed-effect two-stage nested design under variance heterogeneity. The actual significance levels and statistical power of the test statistics were compared in a simulation study. The results show that the proposed procedures maintain better Type I error rate control and have greater statistical power than those obtained by the conventional F test in various conditions. Therefore, the proposed test statistics are recommended in terms of robustness and easy implementation.

• 出版日期2011-5