ANALYZING SMALL SAMPLES OF REPEATED MEASURES DATA WITH THE MIXED-MODEL ADJUSTED F TEST

Jaime Arnau (1) , Roser Bono (1) , Guillermo Vallejo (2)

1 Metodología de las Ciencias del Comportamiento
2 Universidad de Oviedo [Oviedo]

This research examines the Type I error rates obtained when using the mixed model with the Kenward-Roger correction and compares them with the Between-Within and Satterthwaite approaches in split-plot designs. A simulated study was conducted to generate repeated measures data with small samples under normal distribution. The data were obtained via three covariance matrices (unstructured, heterogeneous first-order auto-regressive and random coefficients), the one with the best fit being selected according to the Akaike criterion. The results of the simulation study showed the Kenward-Roger test to be more robust, particularly when the population covariance matrices were unstructured or heterogeneous first-order auto-regressive.

Mots clés: Physical Sciences

Jaime Arnau, Roser Bono, Guillermo Vallejo. ANALYZING SMALL SAMPLES OF REPEATED MEASURES DATA WITH THE MIXED-MODEL ADJUSTED F TEST. Communications in Statistics - Simulation and Computation, 2009, 38 (05), pp.1083-1103. ⟨10.1080/03610910902785746⟩. ⟨hal-00514348⟩