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"We find that the average treatment effect is estimated by the type I and type II key effects, with type I and type II main effects affecting average treatment outcomes, but type III SS yield biased estimates of the average treatment effect when there are interactions. " If interactions are involved, ANOVA type I is always biased, ANOVA type I is always biased, and ANOVA type II and III key results are biased, if interactions are present. ".
Source link: https://europepmc.org/article/MED/35617441
"The use of chemical methods based on variance analysis allows for the determination of the statistical significance of the experimental variables used in a study. " However, classical multivariate ANOVA has a number of features that make it impractical for dealing with metabolomics results, but classical multivariate ANOVA does have a number of limitations, making it impractical for dealing with metabolomics results. However, pertinent variables reported by GASCA tend to be more reliable, given that there is a strong similarity with those variables identified by the widely used partial least squares discriminant analysis method. ".
Source link: https://europepmc.org/article/MED/35630781
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