Search results for "Mixed Mode"
showing 10 items of 72 documents
Using the dglars Package to Estimate a Sparse Generalized Linear Model
2015
dglars is a publicly available R package that implements the method proposed in Augugliaro et al. (J. R. Statist. Soc. B 75(3), 471-498, 2013) developed to study the sparse structure of a generalized linear model (GLM). This method, called dgLARS, is based on a differential geometrical extension of the least angle regression method. The core of the dglars package consists of two algorithms implemented in Fortran 90 to efficiently compute the solution curve. dglars is a publicly available R package that implements the method proposed in Augugliaro et al. (J. R. Statist. Soc. B 75(3), 471-498, 2013) developed to study the sparse structure of a generalized linear model (GLM). This method, call…
Variable selection in mixed models: a graphical approach
2014
Model selection can be defined as the task of estimating the performance of dif- ferent models in order to choose the (approximate) best one. The purpose of this article is to introduce an extension of the graphical representation of deviance proposed in the framework of classical and generalized linear models to the wider class of mixed models. The proposed plot is useful in determining which are the important explanatory variables conditioning on the random effects part. The applicability and the easy interpretation of the graph are illus- trated with a real data examples.
A recap on Linear Mixed Models and their hat-matrices
2017
This working paper has a twofold goal. On one hand, it provides a recap of Linear Mixed Models (LMMs): far from trying to be exhaustive, this first part of the working paper focusses on the derivation of theoretical results on estimation of LMMs that are scattered in the literature or whose mathematical derivation is sometimes missing or too quickly sketched. On the other hand, it discusses various definitions that are available in the literature for the hat-matrix of Linear Mixed Models, showing their limitations and proving their equivalence.
Geographical variation in pharmacological prescription
2009
Promoting rational drug administration in treatments is one of the most important issues in Public Health. Bayesian hierarchical models are a very useful tool for incorporating geographical information into the analysis of pharmacological prescription data. They allow the mapping of spatial components which express the trend of geographical variation. In addition, these models are able to deal with uncertainty in a sequential way through prior distributions on parameters and hyperparameters. Bayes' theorem combines all types of information and provides the posterior distribution which is computed through Markov Chain Monte Carlo (MCMC) simulation methods. Simulated data for pharmacological …
Random effects elliptically distributed in unbalanced linear models
2008
In linear mixed effects models, random effects are used for modelling the variance-covariance structure of the response variable. These models are based on the assumption that the random effects are normally distributed, but in literature alternative random effect distributions have been proposed and the consequences of misspecification are investigated. These studies consider only balanced designs. Aim of this paper is to study an unbalanced linear mixed model with random effects elliptically distributed.
Robust estimation of mean electricity consumption curves by sampling for small areas in presence of missing values
2017
In this thesis, we address the problem of robust estimation of mean or total electricity consumption curves by sampling in a finite population for the entire population and for small areas. We are also interested in estimating mean curves by sampling in presence of partially missing trajectories.Indeed, many studies carried out in the French electricity company EDF, for marketing or power grid management purposes, are based on the analysis of mean or total electricity consumption curves at a fine time scale, for different groups of clients sharing some common characteristics.Because of privacy issues and financial costs, it is not possible to measure the electricity consumption curve of eac…
Removing Batch Effects from Longitudinal Gene Expression - Quantile Normalization Plus ComBat as Best Approach for Microarray Transcriptome Data
2016
International audience; Technical variation plays an important role in microarray-based gene expression studies, and batch effects explain a large proportion of this noise. It is therefore mandatory to eliminate technical variation while maintaining biological variability. Several strategies have been proposed for the removal of batch effects, although they have not been evaluated in large-scale longitudinal gene expression data. In this study, we aimed at identifying a suitable method for batch effect removal in a large study of microarray-based longitudinal gene expression. Monocytic gene expression was measured in 1092 participants of the Gutenberg Health Study at baseline and 5-year fol…
"a priori" Dietary Patterns and Cognitive Function in the SUN Project
2019
<b><i>Objectives:</i></b> To study and compare associations of 5 dietary patterns – Mediterranean dietary pattern (MDP), Dietary Approaches to Stop Hypertension (DASH), Mediterranean-DASH Intervention for Neurodegenerative delay (MIND), Alternative Healthy Eating Index (AHEI-2010), and a pro-vegetarian diet (PVD) – with cognitive function. <b><i>Patients and Methods:</i></b> A subgroup of 806 participants from the “Seguimiento Universidad de Navarra”(SUN) cohort of university graduates, &#x3e;55 years old, was interviewed with the validated Spanish Telephone Interview for Cognitive Status (STICS-m) at baseline and after 2 and 6 years. For …
A Bayesian Approach for Timing the Neolithization in Mediterranean Iberia
2017
AbstractIn this paper, we compile recent14C dates related to the Neolithic transition in Mediterranean Iberia and present a Bayesian chronological approach for testing thedual model, a mixed model proposed to explain the spread of farming and husbandry processes in eastern Iberia. The dual model postulates the coexistence of agricultural pioneers and indigenous Mesolithic foraging groups in the Middle Holocene. We test this general model with more regional models of four geographical areas (Northeast, Upper, and Middle Ebro Valley, and Eastern and South/Southeastern regions) and present a filtered summed probability of all14C dates known in the region in order to compare socioecological dyn…
Bayesian joint models for longitudinal and survival data
2020
This paper takes a quick look at Bayesian joint models (BJM) for longitudinal and survival data. A general formulation for BJM is examined in terms of the sampling distribution of the longitudinal and survival processes, the conditional distribution of the random effects and the prior distribution. Next a basic BJM defined in terms of a mixed linear model and a Cox survival regression models is discussed and some extensions and other Bayesian topics are briefly outlined.