Global ETD Search
Search theses and dissertations gathered from participating repositories worldwide. Every result links back to the library that holds it. No account is needed.
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Showing 1 to 20 of 88 for “"linear mixed model"”.
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Linear Mixed Model Robust Regression
Mixed models are powerful tools for the analysis of clustered data and many extensions of the classical linear mixed model with normally distributed response have been established. As with all parametric models, correctness of the assumed model is critical for the validity of the ensuing inference. …
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Linear mixed model for multi-level omics data
… In the first project, I developed a Bayesian linear mixed model (BLMM), where genetic effects were modelled using a hybrid of the sparsity regression and linear mixed model with multiple random effects. The parameters in BLMM were inferred through a computationally efficient variational Bayes …
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Selecting the Best Linear Mixed Model Using Predictive Approaches
The linear mixed model is widely implemented in the analysis of longitudinal data. Inference techniques and information criteria are available and well-studied for goodness-of-fit within the linear mixed model setting. Predictive approaches such as R-squared, PRESS, and CCC are available for the …
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SafeGENIE: Secure and federated linear mixed model association tests
… important, prevalent class of methods known as linear mixed model (LMM) association tests or would provide limited privacy protection, due to the high computational burden of LMMs under existing secure computation frameworks. Here we introduce SafeGENIE, an efficient and provably secure …
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The LASSO linear mixed model for mapping quantitative trait loci
… methods presented in this thesis. Multiple QTL models have been previously proposed and are likely to be superior to single QTL models. The multiple QTL models can be loosely divided into two categories : 1 ) model building methods that aim to generate good models that contain only a subset of …
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The Generalized Linear Mixed Model for Finite Normal Mixtures with Application to Tendon Fibrilogenesis Data
We propose the generalized linear mixed model for finite normal mixtures (GLMFM), as well as the estimation procedures for the GLMFM model, which are widely applicable to the hierarchical dataset with small number of individual units and multi-modal distributions at the lowest level of clustering. …
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A penalized linear mixed model with generalized method of moments estimators for complex phenotype prediction
Linear mixed models have long been the method of choice for risk prediction analysis on high-dimensional data, where random effect terms are used to capture predictive effects from multiple markers. However, it remains computationally challenging to simultaneously model a large number of variables …
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A variance shift model for outlier detection and estimation in linear and linear mixed models
… are established methods in detecting outliers in linear fixed effects analysis. The extension of these methods to detecting outliers in linear mixed models has not been entirely successful, in the literature. This thesis focuses on a variance shift outlier model as an approach to detecting and …
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Modified BIC for Model Selection in Linear Mixed Models
Linear mixed effects models are widely used in applications to analyze clustered and longitudinal data. Model selection in linear mixed models is more challenging than that of linear models as the parameter vector in a linear mixed model includes both fixed effects and variance components …
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Bidirectional Distribution Reflection Function of Algodones Dunes
… satellite sensors based on a surface reflectance model. Two approaches were taken during this research: a field campaign and laboratory measurements. The first approach, the field campaign, was accomplished with a trip to the Algodones Dunes from the 8th to the 13th of March, 2015. During the …
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Combining measurements with deterministic model outputs: predicting ground-level ozone
The main topic of this thesis is how to combine model outputs from deterministic models with measurements from monitoring stations for air pollutants or other meteorological variables. We consider two different approaches to address this particular problem. The first approach is by using the …
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Data combining using mixtures of g-priors with application on county-level female breast cancer prevalence
… errors. In the first project, data combining of linear models with the classical mixtures of g-priors is investigated. We calculate and compare the posterior estimates and the frequentist properties of the Bayesian estimator from the model with individual and combined data. To resolve the newly …
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Likelihood Theory and Methods for Generalized Linear Mixed Models
Generalized linear mixed models are an essential group of models for analysing many present-day complex data sets, especially those that contain non-normal and correlated response data. Despite the large volume of research concerning this group of models, there is very little theory concerning the …
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An ecological adjusted random effect model for violent and property crime in Windhoek (2011-2016)
… Zero-Inflated Negative Binomial Generalized Linear Mixed Model (ZTNB-GLMM) when observations are correlated in ways that require random effects. The present study investigates ecological factors influencing Violent and Property crime in Windhoek by using data obtained from the Windhoek police …
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The effects of open door policies for community colleges and achieving accountability
… Career and Technical Education Act of 2006, a linear mixed model analysis was performed discovering significant relationships between the core performance indicators and other demographic factors such as, gender, race, students who meet the definition of students with disabilities, students who …
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An analysis of the relationship between alcohol availability and alcohol-related hospital admissions in the city of Chicago, 1990--1997
… individual level characteristics, a generalized linear mixed model was fit using Markov Chain Monte Carlo. The likelihood of a hospital admission being alcohol related was higher in neighborhoods with a greater number of alcohol outlets. These findings suggest that increased regulation of alcohol …
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Semiparametric Bayesian Joint Model With Variable Selection
<p>In longitudinal studies, a popular model is the linear mixed model that includes fixed effects and subject specific random effects. In many clinical trials and other medical and reliability studies, we can often obtain repeated measurements or longitudinal data that includes survival or …
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Exploring the neural link between performance monitoring and emotional responses to social exclusion : an EEG study in an adolescent sample
… may have influenced the findings. Exploratory linear mixed model analyses comparing ERP amplitudes across task conditions were then conducted. Despite nonsignificant findings, this study may contribute to expanding evidence that cognitive processes, such as performance monitoring, might depend …
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Individual and Partner Exercise Status and Cognitive Function in Older Adults
The present study used a linear mixed model analytic approach to assess the association between a combined respondent and spousal exercise score and cognitive outcomes of older adult respondents drawn from a nationally representative dataset, The Health and Retirement Study. Informed by the …
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Statistical methods for outcome misclassification adjustment in causal inference and spatial classification.
… device is not available. Spatial generalized linear mixed model (SGLMM) and indicator kriging (IK) are applied to spatial classification at unsampled locations. In a Bayesian perspective, we propose two-stage methods incorporating validation data into prior elicitation. The proposed …
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