Analyzing repeated measures using resampling methods

Authors

  • Guillermo Vallejo Universidad de Oviedo
  • M. Paula Fernández Universidad de Oviedo
  • Ellián Tuero Universidad de Oviedo
  • Pablo E. Livacic Rojas Universidad de Santiago (Chile)
Keywords: robustness, multisample sphericity, theoretical critical values, empirical critical values

Abstract

This article evaluated the robustness of several approaches for analyzing repeated measures designs when the assumptions of normality and multisample sphericity are violated separately and jointly. Specifically, the authors’ work compares the performance of two resampling methods, bootstrapping and permutation tests, with the performance of the usual analysis of variance (ANOVA) model and the mixed linear model procedure ad-justed by the Kenward–Roger solution available in SAS PROC MIXED. The authors found that the permutation test outperformed the other three methods when normality and sphericity assumptions did not hold. In contrast, when normality and multisample sphericity assumptions were violated the results clearly revealed that the Bootstrap-F test provided generally better control of Type I error rates than the permutation test and mixed linear model approach. The execution of ANOVA approach was considerably influenced by the presence of heterogeneity and lack of spheric-ity, but scarcely affected by the absence of normality.

Downloads

Download data is not yet available.
How to Cite
Vallejo, G., Fernández, M. P., Tuero, E., & Livacic Rojas, P. E. (2010). Analyzing repeated measures using resampling methods. Anales de Psicología / Annals of Psychology, 26(2), 400–409. Retrieved from https://revistas.um.es/analesps/article/view/109411
Issue
Vol. 26 No. 2 (2010)
Section
Methodology

 

The works published in this journal are subject to the following terms:
1. The Publications Service of the University of Murcia (the publisher) retains the property rights (copyright) of published works, and encourages and enables the reuse of the same under the license specified in paragraph 2.

© Servicio de Publicaciones, Universidad de Murcia, 2022

2. The works are published in the online edition of the journal under a Creative Commons Reconocimiento-CompartirIgual 4.0 (legal text). You can copy, use, distribute, transmit and publicly display, provided that: i) you cite the author and the original source of publication (journal, editorial and URL of the work), ii) are not used for commercial purposes, iii ) mentions the existence and specifications of this license.


This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.

3. Conditions of self-archiving. Is allowed and encouraged the authors to disseminate electronically pre-print versions (version before being evaluated and sent to the journal) and / or post-print (version reviewed and accepted for publication) of their works before publication, as it encourages its earliest circulation and diffusion and thus a possible increase in its citation and scope between the academic community. RoMEO Color: Green.