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.
Results
Showing 1 to 20 of 114 for “"Mixed Effects Models"”.
-
Linear mixed effects models in functional data analysis
Regression models with a scalar response and a functional predictor have been extensively studied. One approach is to approximate the functional predictor using basis function or eigenfunction expansions. In the expansion, the coefficient vector can either be fixed or random. The random coefficient …
-
Analysis of gender wage gap using mixed effects models
… each job title using a novel approach: linear mixed effects regression. The linear mixed effects model captures both systematic trends and unexplained variability simultaneously to provide a more comprehensive understanding of the gender wage gap. Here are the key findings: 1. The unexplained …
-
Modelling growth patterns of bird species using non-linear mixed effects models
… such as polynomial regressions, non-parametric models and non-linear mixed effects models have been used to fit models to growth data. In recent years, non-linear mixed effects models have become an important tool for growth models. We have fitted univariate inverse exponential, Gompertz, …
-
Fiducial Inference for Mixed-Effects Models: A Frequentist Advancement for Small-Sample Problems
… a comprehensive fiducial inference framework for mixed-effects models, offering a robust frequentist alternative for statistical inference in small-sample settings. Traditional methods such as maximum likelihood estimation (MLE), Wald-type intervals, and bootstrap techniques often fail to provide …
-
On the Use of Mixed -Effects Models for the Analysis of Probability Judgments
… judgment model which is expressed as a mixed-effects ordinal probit regression model. This model can be used to derive several new model-based measures of external correspondence as well as establishing a means of deriving the sampling/posterior distributions of such measures. Issues of …
-
Predicting Changes in Individual Wellbeing Scores: Mixed Effects Models using Sleep Data from Wearables
… nature of wellbeing assessments, we employ mixed effects modeling techniques where each individual is treated as their own cluster, including Linear Mixed Effects models (LMM) and Mixed Effects Random Forest (MERF), where the latter is benchmarked against classic machine learning models. The …
-
Nonparametric testing for random effects in mixed effects models based on the piecewise linear interpolate of the log characteristic function
Traditional linear mixed effect models assume the distributions of the random effects and errors follow normal distribution with mean zero and homoscedastic variance sigma square. This thesis presents a new nonparametric testing approach for normality for the random effects distribution based on …
-
Application of Regression Spline in Multilevel Longitudinal Modeling
A general description of linear mixed-effects models, linear mixed-effects models for longitudinal data, and regression splines are first reviewed. Subsequently, a methodology that applies regression spline in multilevel longitudinal modeling is proposed to deal with the longitudinal data with …
-
Extracting Feature Vectors From Event-Related fMRI Data to Enable Machine Learning Analysis
Linear models are the dominant means of extracting summaries of events in fMRI for feature vector based machine learning. While they are both useful and robust, they are limited by the assumptions made in modeling. In this work, we examine a number of feature extraction techniques adjacent to …
-
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 …
-
Spatial and temporal heterogeneity in life history and productivity trends of Atlantic Weakfish (Cynoscion regalis) and implications to fisheries management
… largely ignore this heterogeneity in their models. This thesis addresses the effects of spatial and temporal heterogeneity on stock assessment models using Atlantic Weakfish (Cynoscion regalis) as a case study. First, spatial and temporal variation was incorporated into length-, weight-, and …
-
Accounting for Correlation in the Analysis of Randomized Controlled Trials with Multiple Layers of Clustering
… make proper statistical inference. Further, the effects of outliers in a multi-center, randomized controlled trial with multiple layers of clustering are examined and strategies for detecting and dealing with outlying observations and clusters are discussed.
-
Debiasing reasoning : a signal detection analysis
… bias. These measures are then analysed using mixed effects models. Chapter 1 gives a general introduction to the topic, and outlines the content of subsequent chapters. In Chapter 2, I review the psychological literature around belief bias, the growth of the use of SDT models, and approaches …
-
Modeling longitudinal data with interval censored anchoring events
… not be able to use the traditional longitudinal models to describe the temporal changes as desired. Existing methods often make either ad hoc or strong assumptions on the anchoring events, which are unveri able and prone to biased estimation and invalid inference. Although not able to directly …
-
Outcome selection in longitudinal analysis of immunological data
… modelling frameworks. Generalised linear mixed-effects models are better suited to the characteristics of immunological data and research than linear mixed-effects models. Two dimension reduction techniques are compared: principal component analysis (PCA) and hierarchical cluster analysis …
-
Quantifying Ungulate-Rangeland Interactions: From Monitoring Free-Roaming Horse Condition to Vegetation Response Following Herbivore Exclusion
… exclusion of ungulates and jackrabbits. Bayesian mixed-effects models reveal that ungulate exclusion increased winterfat, cyanobacteria, lichen, moss, and annual cover while decreasing soil compaction. Rabbit exclusion further increased winterfat and annual forb cover while decreasing annual …
-
Some new types of designs with applications in conjoint analysis
… analysis. Appropriateness of random and mixed effects models, which are different from traditional fixed effects models used for analyzing CA data, is highlighted in several examples.
-
The role of teachers in classroom peer networks
… victimization over time. Meta-analytic random effects and mixed effects models were applied via ‘metaphor’ package to test the moderating role of early teacher-student interactions quality, which was observed using Classroom Assessment Scoring System (CLASS), on the yearlong classroom social …
Page 1 of 6