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LiMM-PCA : combining ASCA+ and linear mixed models to analyse high dimensional designed data

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  • Martin, Manon
  • Govaerts, Bernadette

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  • Martin, Manon & Govaerts, Bernadette, 2019. "LiMM-PCA : combining ASCA+ and linear mixed models to analyse high dimensional designed data," LIDAM Discussion Papers ISBA 2019021, Université catholique de Louvain, Institute of Statistics, Biostatistics and Actuarial Sciences (ISBA).
    • Handle: RePEc:aiz:louvad:2019021
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    References listed on IDEAS

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    1. Halekoh, Ulrich & Højsgaard, Søren, 2014. "A Kenward-Roger Approximation and Parametric Bootstrap Methods for Tests in Linear Mixed Models The R Package pbkrtest," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 59(i09).
    2. Guisset, Severine & Martin, Manon & Govaerts, Bernadette, 2019. "Comparison of PARAFASCA, AComDim, and AMOPLS approaches in the multivariate GLM modelling of multi-factorial designs," LIDAM Reprints ISBA 2019004, Université catholique de Louvain, Institute of Statistics, Biostatistics and Actuarial Sciences (ISBA).
    3. Thiel, Michel & Feraud, Baptiste & Govaerts, Bernadette, 2017. "ASCA+ and APCA+: Extensions of ASCA and APCA in the analysis of unbalanced multifactorial designs," LIDAM Reprints ISBA 2017023, Université catholique de Louvain, Institute of Statistics, Biostatistics and Actuarial Sciences (ISBA).
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    1. Govaerts, B. & Francq, B. & Marion, R. & Martin, M. & Thiel, M., 2020. "The essentials on linear regression, ANOVA, general linear and linear mixed models for the chemist," LIDAM Discussion Papers ISBA 2020012, Université catholique de Louvain, Institute of Statistics, Biostatistics and Actuarial Sciences (ISBA).

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