Manon Martin -

The primary goal of Martin’s research is to bridge the gap between complex experimental designs (e.g., multifactorial, longitudinal, or unbalanced designs) and the analysis of high-dimensional data, such as NMR spectra or mass spectrometry. She develops methods that allow scientists to extract meaningful biological insights from data that would otherwise be confounded by noise or complex variables.

: Martin has significantly advanced the ASCA (ANOVA-Simultaneous Component Analysis) family of methods. Her work on LiMM-PCA combines Linear Mixed Models (LMM) with Principal Component Analysis (PCA) to handle advanced designs with random effects and quantitative variables. manon martin

Below is a structured "paper" summarizing the core pillars of her scientific contributions and research focus. The primary goal of Martin’s research is to

: She has authored accessible guides on Linear Regression, ANOVA, and Linear Mixed Models tailored specifically for chemists and life-science researchers. 4. Application Domains Her work on LiMM-PCA combines Linear Mixed Models

Manon Martin, PhD Primary Institution: UCLouvain, Institute of Statistics, Biostatistics and Actuarial Sciences (ISBA) 1. Core Research Objective

: She has compared and enhanced techniques like AMOPLS and AComDim , extending them to unbalanced experimental designs using Generalized Linear Model (GLM) versions of matrix decomposition.