Data analysis of incomplete repeated measures using a multivariate extension of the Brown-Forsythe procedure

  1. Guillermo Vallejo Seco 1
  2. María Paula Fernández García 1
  3. Pablo Esteban Livacic Rojas 2
  4. Ellián Tuero Herrero 1
  1. 1 Universidad de Oviedo
    info

    Universidad de Oviedo

    Oviedo, España

    ROR https://ror.org/006gksa02

  2. 2 Universidad de Santiago de Chile
    info

    Universidad de Santiago de Chile

    Santiago de Chile, Chile

    ROR https://ror.org/02ma57s91

Aldizkaria:
Psicothema

ISSN: 0214-9915

Argitalpen urtea: 2018

Alea: 30

Zenbakia: 4

Orrialdeak: 434-441

Mota: Artikulua

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Beste argitalpen batzuk: Psicothema

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Background: A multivariate extension of the Brown-Forsythe (MBF) procedure can be used for the analysis of partially repeated measure designs (PRMD) when the covariance matrices are arbitrary. However, the MBF procedure requires complete data over time for each subject, which is a significant limitation of this procedure. This article provides the rules for pooling the results obtained after applying the same MBF analysis to each of the imputed datasets of a PRMD. Method: Montecarlo methods are used to evaluate the proposed solution (MI-MBF), in terms of control of Type I and Type II errors. For comparative purposes, the MBF analysis based on the complete original dataset (OD-MBF) and the covariance pattern model based on an unstructured matrix (CPM-UN) were studied. Results: Robustness and power results showed that the MI-MBF method performed slightly worse than tests based on CPM-UN when the homogeneity assumption was met, but slightly better when that assumption was not met. We also note that without assuming equality of covariance matrices, little power was sacrificed by using the MI-MBF method in place of the OD-MBF method. Conclusions: The results of this study suggest that the MI-MBF method performs well and could be of practical use.

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We thank the three anonymous reviewers for valuable comments and suggestions. This research was supported by grant PSI-2015-67630-PSIC (AEI/FEDER, UE) from the Spanish Ministry of Economy and Competitiveness, and by grant 1170642 (FONDECYT) from the Chilean National Fund for Scientific and Technological Development.

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