Manon Martin, PhD Primary Institution: UCLouvain, Institute of Statistics, Biostatistics and Actuarial Sciences (ISBA) 1. Core Research Objective
: An R package designed for the linear modeling of high-dimensional designed data based on the ASCA/APCA family. manon martin
Below is a structured "paper" summarizing the core pillars of her scientific contributions and research focus. : She has authored accessible guides on Linear
: She has authored accessible guides on Linear Regression, ANOVA, and Linear Mixed Models tailored specifically for chemists and life-science researchers. 4. Application Domains She develops methods that allow scientists to extract
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.