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Eq-DIAGNOBATCH, a Shiny application for topical product equivalence with batch effect and multivariate outlier analysis

MONLEON-GETINO, T.; Ocana Rebull, J.

2024-12-20 pharmacology and therapeutics
10.1101/2024.12.16.24319103 medRxiv
Show abstract

The Eq-DIAGNOBATCH application presented here complements a previous theoretical article about establishing the equivalence of topical products in a parallel linear model, accounting for a batch effect or not. This application provides a very simple way of carrying out the equivalence test for this type of situation, efficiently obtaining the estimates of the parameters of interest (equivalence intervals, geometric mean ratio, and variance components), and allowing calculations to be performed assuming a batch effect or not. It also examines the statistical implications of the presence of outliers in the sample, from both a univariate and multivariate point of view. The operation and mode of use of Eq-DIAGNOBATCH are presented, including examples related with the quality and equivalence of topical products and bioequivalence analysis. Some of these examples come from the literature and others from real-life industry case studies.

Matching journals

The top 10 journals account for 50% of the predicted probability mass.

1
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"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.