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Modelling finger force produced from different tasks using linear mixed models with lme R function

Caroline Bazzoli 1 Frédérique Letué 1 Marie-José Martinez 2
1 SAM - Statistique Apprentissage Machine
LJK - Laboratoire Jean Kuntzmann
2 MISTIS - Modelling and Inference of Complex and Structured Stochastic Systems
Inria Grenoble - Rhône-Alpes, LJK - Laboratoire Jean Kuntzmann, INPG - Institut National Polytechnique de Grenoble
Abstract : The biomechanical data considered in this paper are obtained from a study carried out to understand the coordination patterns of finger forces produced from different tasks. This data cannot be considered independent because of within-individual repeated measurements, and because of simultaneous finger measurements. To fit these data, we propose a methodology focused on linear mixed models. Different random effects structures and complex variance-covariance matrices of the error are considered. We highlight how to use the lme R function to deal with such a modelling. The paper is accessible to an audience experienced with linear models. Some familiarity with the R software is also helpful.
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Caroline Bazzoli, Frédérique Letué, Marie-José Martinez. Modelling finger force produced from different tasks using linear mixed models with lme R function. Case Studies in Business, Industry and Government Statistics, Société Française de Statistique, 2015, 6 (1), pp.16-36. ⟨hal-00998910⟩

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