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 15 of 15 for “"Generalized Linear Model (GLM)."”.
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Analysis of the Repeated Measurement Data using the Hierarchical Clustering and Nonlinear Regression Methods in Asthma Pharmacogenetic Study
… Korea asthmatics and tried to develop a clinical model to predict the drug response to asthma drug. BACKGROUND: Long acting β2-agonists (LABA) is the most powerful bronchodilator and inhaled corticosteroid (ICS) was the most effective anti-inflammatory drug currently available in asthma …
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Covariate-adjusted ROC regressions and the extensions in trend tests.
… a binary classifier for continuous outcomes. A generalized linear model (GLM) framework enabled one to investigate covariate effects to model the ROC using parametric and semi-parametric regression methods. The latest addition to this ongoing investigation into problems of this type made use of …
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Semiparametric Regression Methods with Covariate Measurement Error
… in the covariates of two types of regression models. For each we propose a fully Bayesian approach that treats the variable measured with error as a latent variable to be integrated over, and a semi-Bayesian approach which uses a first order Laplace approximation to marginalize the variable …
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A Longitudinal Analysis of Spanish Morphosyntactic Performance Based on Spanish-English Bilingual Exposure and Usage
… DLD group than in the TD group. Results of the generalized linear model (GLM) of the accuracy of three grammatical markers indicate that the contributing factors differ by the marker: language exposure, language usage, language ability group and grade level have significant effects on accuracy …
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Does CEO Compensation Encourage Risk-Taking? Empirical Evidence from FTSE350.
… empirical analysis using random effect, generalized linear model (GLM), generalized method of moments (GMM), and Robust panel regression. We find that performance-related compensation reduces corporate risk-taking. We also find that based (fixed) salary has a significant and positive …
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Model-based clustering for multivariate time series of counts
This dissertation develops a modeling framework for univariate and multivariate zero-inflated time series of counts and applies the models in a clustering scheme to identify groups of count series with similar behavior. The basic modeling framework used is observation-driven Poisson regression with …
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STATISTICAL FOUNDATIONS OF SINGLE CELL OPEN CHROMATIN ASSAYS
… or quantitative. We also developed a Probability model of Accessible Chromatin in Single cells (PACS), which aims to conduct differential testing while addressing the sparsity and presence of multiple causal factors in complex datasets. By introducing a missing-data-corrected Cumulative Logistic …
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Retrospective analysis of treated prevalence, psychiatric comorbidity prevalence, and healthcare utilization and expenditures in commercially insured children diagnosed with autism spectrum disorder
… rates were generated for 819 ZIP3 regions, and a generalized linear model (GLM) was used to explain geographic variation in prevalence. Aims two and three were addressed in a separate cohort of ASD patients (n=17,787) matched to a non-ASD control group (n=35,574). Three sets of GLMs were fit to …
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Semiparametric Methods for the Generalized Linear Model
The generalized linear model (GLM) is a popular model in many research areas. In the GLM, each outcome of the dependent variable is assumed to be generated from a particular distribution function in the exponential family. The mean of the distribution depends on the independent variables. The link …
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Relational Outlier Detection: Techniques and Applications
… on only numerical data, modern outlier detection models must be able to handle data in various types and structures. Detecting relational outliers should consider (1) Dependencies among different data types, (2) Data types that are not continuous or do not have ordinal characteristics, such as …
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Methods for studying the neural code in high dimensions
… address the challenge of developing and testing models that are both flexible and computationally tractable when used with high dimensional data. In chapter 2 I will discuss an approximation to the generalized linear model (GLM) log-likelihood that I developed in collaboration with my thesis …
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Quantifying syntactic priming in oral production : a corpus-based investigation into dyadic interaction of L1-L1 and L2-L2 speakers of English
… of English. Binary logistic regressions from a generalized linear model (GLM) are employed to disentangle the priming effect from other factors that might be predictors for the target. The analysis of all three constructions controls for interaction between primes and prime-target pair …
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Exploration and development of crash modification factors and functions for single and multiple treatments
… multivariate adaptive regression splines (MARS) modeling is proposed to avoid the over-estimation problem through consideration of interaction impacts between variables in this dissertation. Second, the variation of CMFs with different roadway characteristics among treated sites over time is …
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Cost of Illness Study of Anxiety Disorders for the Ambulatory Adult Population of the United States
… Several multivariate regression analyses, using generalized linear models, were conducted to calculate the overall incremental direct medical costs associated with anxiety disorders, as well as cost by healthcare delivery setting, and cost for different sub-populations. Indirect costs were …
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Survival of adults with HIV-1 infection or Type 2 diabetes in the South African private sector
… healthcare practitioners, ART programmes, other modellers, insurers and policymakers to understand the prognosis when measured from later durations on ART based on current characteristics. However, most South African studies are based on baseline characteristics, short follow-up times, and low …