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 352 for “"Random effects"”.
-
Inference for general random effects models
… work describes methods associated with general random effects models. Part one describes a technique for investigating mean-variance relationships in random effects models. Part two derives and approximation to the likelihood function using a Laplace expansion to the fourth order.
-
A nested random effects model analysis of child survival in Malawi
… model which includes family and community random effects in addition to the fixed effect of the covariates. The parameters of the model are estimated using the Gibbs sampler, a Bayesian Markov Chain Monte Carlo (MCMC) method. We believe this to be the first time the method has been used for …
-
A Normal-Mixture Model with Random-Effects for RR-Interval Data
In many applications of random-effects models to longitudinal data, such as heart rate variability (HRV) data, a normal-mixture distribution seems to be more appropriate than the normal distribution assumption. While the random-effects methodology is well developed for several distributions in the …
-
A Bayesian solution to non-convergence of crossed random effects models
… combinations of subjects and stimuli, crossed random effects models simultaneously take into account both fixed effects and random effects of the subjects and stimuli; however, maximum likelihood estimation (MLE) and restricted maximum likelihood (REML) estimation often encounter convergence …
-
Profile Monitoring with Fixed and Random Effects using Nonparametric and Semiparametric Methods
… monitor the fitted profiles or the estimated random effects over time to determine if there have been changes in the profiles. The majority of previous studies in profile monitoring focused on the parametric modeling of either linear or nonlinear profiles, with both fixed and random effects, …
-
Random Effects Selection In Bayesian Accelerated Failure Time Model With Correlated Interval Censored Data
… of interpretation. Variable selection and often random effect selection in case of clustered data becomes crucial in such applications. We propose a Bayesian method for random effects selection in mixed effects accelerated failure time models. The proposed method relies on Cholesky decomposition …
-
A Bayesian approach to crossed-random-effects mediation analysis for zero-inflated mediators and binary outcomes
In crossed random effects designs, observations are nested in the combination of two random factors, e.g., subjects and stimuli. Such designs are popular in experimental research in social sciences. Crossed random effects models (CREM) can accommodate the random effects of both subjects and …
-
Nonparametric testing for random effects in mixed effects models based on the piecewise linear interpolate of the log characteristic function
… 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 the piecewise linear …
-
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 …
-
Linear mixed effects models in functional data analysis
… the coefficient vector can either be fixed or random. The random coefficient vector is also known as random effects and thus the regression models are in a mixed effects framework. The random effects provide a model for the within individual covariance of the observations. But it also …
-
Semiparametric Bayesian Joint Model With Variable Selection
… 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 time-to-event histories. Recently, methods for …
-
Mixed Effects Modeling and Correlation Structure Selection for High Dimensional Correlated Data
… thesis: mixed-effect modeling with unspecified random effects and correlation structure selection for high-dimensional data. In longitudinal studies, mixed-effects models are important for addressing subject-specific effects. However, most existing approaches assume normal distributions for the …
-
Clustering Profiles in Generalized Linear Mixed Models Settings Using Bayesian Nonparametric Statistics
… models consist of two sets of parameters: fixed effects parameters that associate covariates to the response at the population level, and random effects parameters that associate covariates to the response at the individual level. We introduce a method that identifies homogeneous groups in the …
-
Some Advanced Semiparametric Single-index Modeling for Spatially-Temporally Correlated Data
… nonparametric function and spatially correlated random effects, while the other does not separate the nonparametric function and spatially correlated random effects. We estimate these two models using two algorithms based on Markov Chain Expectation Maximization algorithm. Our approaches are …
-
Meta-analytische Verfahren zur Auswertung gemeindebezogener Interventionsstudien am Beispiel der deutschen Herz-Kreislauf-Präventionsstudie
… die Berücksichtigung der Heterogenität in der random effects Meta-Analyse zu vergleichbarer Varianzschätzung führt wie die Berücksichtigung der Korrelation im gemischten Modell, ein für solche Studien anerkanntes statistisches Verfahren. Die Vergrößerung der Varianz durch Berücksichtigung der …
-
Statins and Risk of Alzheimer Disease: A Systematic Review and Meta-Analysis
… The objective of this research was to assess the effects of statins in the prevention of Alzheimer disease.</p><p>Methods: A systematic review of MEDLINE (PubMed) was performed to identify all available published prospective studies that evaluated the effect of statin treatment on the incidence of …
-
Statistical Methods for Multi-type Recurrent Event Data Based on Monte Carlo EM Algorithms and Copula Frailties
… events model with multivariate Gaussian random effects (frailties) for the intensity functions. In this chapter, we present nonparametric baseline intensity functions and a multivariate Gaussian distribution for the multivariate correlated random effects. An MCEM algorithm with MCMC …
-
Bayesian modelling of mixed outcome types using random effect.
… and continuous responses simultaneously using random effects. We also extend these models to overcome the bias in parameter estimation due to ignorance of skewness of the continuous response, a misclassified covariate, and a zero-inflated discrete response. Simulation studies indicate that our …
Page 1 of 18