Advancements in multivariate analysis of variance
نویسندگان
چکیده
The Journal of Chemometrics is pleased to announce a special issue focused on multivariate analysis data from designed experiments. ANOVA (Analysis Variance) the standard method for analyzing experimental designs. classical methods are however univariate and do not handle multiple collinear response variables. Designed experiments with outputs prevalent across various scientific disciplines, necessitating that appropriately consider both design nature data. Several techniques have been presented already. most approaches involve combining PCA (principal component analysis) or other exploratory component-based in different ways. Some commonly used this context include ASCA, ANOVA-PCA, AComDim, fifty-fifty MANOVA. These integrate ways extract meaningful information Additionally, there alternative replace partial least squares (PLS) regression, which allows utilization PLS-specific validation variable importance routines. One major advantage all these they only offer interpretation metrics latent variable-based but also provide estimates effect sizes accompanied by corresponding significance testing. Despite progress made recent years, field still young. open questions remain unanswered, need make methodology available broader audience. aim was therefore stimulate explore advances methods, applications, software ANOVA. collection papers includes methodical improvements, practical tutorial, demonstration. Application areas range spectroscopic control fermentation processes metabolomics gene expressions. Overall, showcases power applicability wide domains.
منابع مشابه
Multivariate Analysis of Variance
We provide an expository presentation of multivariate analysis of variance (MANOVA) for both consumers of research and investigators by capitalizing on its relation to univariate analysis of variance models. We address several questions: (a) Why should one use MANOVA. 9 (b) What is the structure of MANOVA? (C) How are MANOVA test statistics obtained and interpreted? (d) How are MANOVA follow-up...
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MOTIVATION Gene class testing (GCT) or gene set analysis (GSA) is a statistical approach to determine whether some functionally predefined sets of genes express differently under different experimental conditions. Shortcomings of the Fisher's exact test for the overrepresentation analysis are illustrated by an example. Most alternative GSA methods are developed for data collected from two exper...
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ژورنال
عنوان ژورنال: Journal of Chemometrics
سال: 2023
ISSN: ['1099-128X', '0886-9383']
DOI: https://doi.org/10.1002/cem.3504