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The Essentials on Linear Regression, ANOVA, General Linear and Linear Mixed Models for the Chemist

Author

Listed:
  • Govaerts, Bernadette

    (Université catholique de Louvain, LIDAM/ISBA, Belgium)

  • Francq, Bernard G.

    (Université catholique de Louvain, LIDAM/ISBA, Belgium)

  • Marion, Rebecca

    (Université catholique de Louvain, LIDAM/ISBA, Belgium)

  • Martin, Manon

    (Université catholique de Louvain, LIDAM/ISBA, Belgium)

  • Thiel, Michel

    (Université catholique de Louvain, LIDAM/ISBA, Belgium)

Abstract

This article provides a brief and accessible guide for implementing general, ANOVA and linear mixed models for the analysis of real world data from chemistry, industrial, bio or life-sciences experiments. The reader is introduced to the main concepts and vocabulary of the subject and to the main statistical methods available for formalizing, estimating and performing statistical inference on these models. Mathematical notations are not avoided but kept accessible, methods are illustrated on several detailed applications and the use of appropriate computer software is discussed.

Suggested Citation

  • Govaerts, Bernadette & Francq, Bernard G. & Marion, Rebecca & Martin, Manon & Thiel, Michel, 2020. "The Essentials on Linear Regression, ANOVA, General Linear and Linear Mixed Models for the Chemist," LIDAM Reprints ISBA 2020011, Université catholique de Louvain, Institute of Statistics, Biostatistics and Actuarial Sciences (ISBA).
    • Handle: RePEc:aiz:louvar:2020011
    DOI: https://doi.org/10.1016/b978-0-12-409547-2.14579-2
    Note: In: 2nd Edition, Comprehensive Chemometrics, Chemical and Biochemical Data Analysis, Elsevier 2020, p. 431-463
    as

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