نتایج جستجو برای: linear mixed effects modelling lmm
تعداد نتایج: 2289214 فیلتر نتایج به سال:
Abstract We analysed the effects of weather and climatic patterns on productivity White Stork in Hungary between 1958 2017, using i) linear mixed effect models (LMM), ii) LMM-s extended by a single random variable or nested combination; iii) fixed iv) an additive model selected variables. As preselection, following variables were identified with substantial support: March mean temperature, prec...
This paper discusses the use of Linear Mixed Models (LMM) and Generalized Linear Mixed Models (GLMM) to predict the wear and damage trajectories of railway wheelsets for a fleet of modern multiple unit trains. The wear trajectory is described by the evolution of the wheel flange thickness, the flange height and the tread diameter; whereas the damage trajectory is assessed through the probabilit...
The linear mixed model (LMM) is a popular statistical for the analysis of longitudinal data. However, robust estimation and inferential conclusions LMM in presence outliers (i.e., observations with very low probability occurrence under Normality) not part mainstream data analysis. In this work, we compared coverage rates confidence intervals (CIs) ba...
BACKGROUND Linear mixed effects models (LMMs) are a common approach for analyzing longitudinal data in a variety of settings. Although LMMs may be applied to complex data structures, such as settings where mediators are present, it is unclear whether they perform well relative to methods for mediational analyses such as structural equation models (SEMs), which have obvious appeal in such settin...
This thesis describes the development of a software prototype implemented in Matlab for non-linear mixed effects modelling based on stochastic differential equations (SDEs). The setup aims at modelling measurements originating from more than one individual and it represents a powerful way of modelling systems with complicated and partially unknown dynamics. The incorporation of SDEs enables the...
BACKGROUND The low (LF) vs. high (HF) frequency energy ratio, computed from the spectral decomposition of heart beat intervals, has become a major tool in cardiac autonomic system control and sympatho-vagal balance studies. The (statistical) distributions of response variables designed from ratios of two quantities, such as the LF/HF ratio, are likely to non-normal, hence preventing e.g., from ...
The general linear model (glm) provides a general framework for a large set of models whose common goal is to explain or predict a quantitative dependent variable by a set of independent variables which can be categorical of quantitative. The glm encompasses techniques such as Student’s t test, simple and multiple linear regression, analysis of variance, and covariance analysis. The glm is adeq...
Motivation: Exploring the genetic basis of heritable traits remains one of the central challenges in biomedical research. In traits with simple mendelian architectures, single polymorphic loci explain a significant fraction of the phenotypic variability. However, many traits of interest appear to be subject to multifactorial control by groups of genetic loci. Accurate detection of such multivar...
AIM The goal of this study was to identify progressing periodontal sites by applying linear mixed models (LMM) to longitudinal measurements of clinical attachment loss (CAL). METHODS Ninety-three periodontally healthy and 236 periodontitis subjects had their CAL measured bi-monthly for 12 months. The proportions of sites demonstrating increases in CAL from baseline above specified thresholds ...
We propose and study a unified procedure for variable selection in partially linear models. A new type of double-penalized least squares is formulated, using the smoothing spline to estimate the nonparametric part and applying a shrinkage penalty on parametric components to achieve model parsimony. Theoretically we show that, with proper choices of the smoothing and regularization parameters, t...
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