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  1. analyticalsciencejournals.onlinelibrary.wiley.com

    Aug 26, 2024In previous work [], we introduced the simulated power curves in ASCA as a strategy to optimize an ASCA pipeline for a specific experimental design in terms of statistical power.Simulated power curves can be used to find the optimal ASCA model in terms of fixed/random factors, crossed/nested relationships, interactions, test statistic, transformations, and others.
  2. analyticalsciencejournals.onlinelibrary.wiley.com

    distributions. The derivation of power curves based on ASCA's permutation testing necessarily requires numerical approaches. In previous work [ 6], we introduced the simulated power curves in ASCA as a strategy to optimize an ASCA pipeline for a spe-cific experimental design in terms of statistical power. Simulated
  3. Mar 1, 2024In this paper, we revisit the Power Curves in ANOVA Simultaneous Component Analysis (ASCA) based on permutation testing, and introduce the Population Curves derived from population parameters describing the relative effect among factors and interactions. We distinguish Relative from Absolute Population Curves, where the former represent statistical power in terms of the normalized effect size ...
  4. The derivation of Power Curves based on ASCA's permutation testing necessarily requires numerical approaches. In previous work camacho2023permutation , we introduced the simulated Power Curves in ASCA as a strategy to optimize an ASCA pipeline for a specific experimental design in terms of statistical power. Simulated Power Curves can be used ...
  5. analyticalsciencejournals.onlinelibrary.wiley.com

    Aug 26, 2024Both types of population curves allow us to make decisions regarding the number and nature (fixed/random) of factors, their relationships (crossed/nested), and the number of levels and replicates, among others, in an multivariate experimental design (e.g., an omics study) during the planning phase of the experiment.
  6. ui.adsabs.harvard.edu

    In this paper, we revisit the Power Curves in ANOVA Simultaneous Component Analysis (ASCA) based on permutation testing, and introduce the Population Curves derived from population parameters describing the relative effect among factors and interactions. We distinguish Relative from Absolute Population Curves, where the former represent statistical power in terms of the normalized effect size ...
  7. paperswithcode.com

    Mar 1, 2024Population Power Curves in ASCA with Permutation Testing 1 Mar 2024 ... Relative Population Curves are useful to find the optimal ASCA model (e.g., fixed/random factors, crossed/nested relationships, interactions, the test statistic, transformations, etc.) for the analysis of an experimental design at hand. Absolute Population Curves are useful ...
  8. semanticscholar.org

    In this paper, we revisit the power curves in ANOVA simultaneous component analysis (ASCA) based on permutation testing and introduce the population curves derived from population parameters describing the relative effect among factors and interactions. The relative effect has important practical implications: The statistical power of a given factor depends on the design of other factors in ...

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