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 22 for “"Overdispersion"”.
-
Rna-Sequencing Applications: Gene Expression Quantification and Methylator Phenotype Identification
… The first is the methodology for modeling the overdispersion inherent in RNA-seq data for differential expression analysis. This aspect is addressed in three sections. The second aspect is the application of RNA-seq data to identify the CpG island methylator phenotype (CIMP) by integrating …
-
Spatial Poisson regression : Bayesian approach correcting for measurement error with applications.
… and many other areas of research. Furthermore, overdispersion is another common problem that plagues count data. McBride (2006) proposed a Bayesian Poisson regression model which accounts for overdispersion in count data. We extend this model by adding parameters to accommodate the problems …
-
Birth spacing and child mortality in Mozambique : evidence from two demographic and health surveys
… regression model is applied to account for the overdispersion present in the Poisson model.
-
Causal Inference Methods for Microbiome Data
… characterized by high dimensionality, sparsity, overdispersion, and strong interdependencies, making conventional mediation approaches ill-suited for reliable inference. Existing methods often fail to deliver valid interval estimates or to capture longitudinal dynamics, especially when indirect …
-
A Piecewise Linear Generalized Poisson Regression Approach to Modeling Longitudinal Frequency Data
… (and detect) underdispersion, equidispersion, or overdispersion in the data. We apply this model to frequency data collected from a clinical trial studying the symptoms of menopausal women. A simulation study that implements a generalized Poisson model for</p><p> univariate data is also provided.
-
An Investigation of Answer Changing on a Large-Scale Computer-Based Educational Assessment
… a better approach than Poisson regression due to overdispersion in the Poisson models. Student demographic variables were not useful in explaining answer-changing behaviors, for any of the independent variables examined. Results also add to the field’s understanding of answer-changing and …
-
Semiparametric Bayesian Count Data Models
… extended the Poisson distribution to account for overdispersion and/or zero inflation. Additionally we have incorporated corresponding components in structured additive form into the predictor. The models are fully Bayesian and inference is carried out by computationally efficient MCMC techniques. …
-
Computational and Statistical Methods for Analysis of Spatial Transcriptomics Data
… including additive mixtures of single cells, overdispersion, and technical platform effects across technologies. The key contributions of this thesis include developing a statistical framework accounting for these challenges to identify cell types within spatial transcriptomics datasets. We …
-
Associated factor of mortality rate amongst patients with AIDS and HIV-TB co-infections using zero inflated negative binomial method
… Negative Binomial has been suggested when overdispersion is present. It is more appropriate than the classical Negative Binomial regression model. Hence, this thesis follows the general objective, that is to compare Zero-Inflated Negative Binomial and Negative Binomial in identifying …
-
Regression analysis for estimation of the influencing factors on road accident injuries in Oman Poisson Regression Model and Poisson Alternatives
… Accident data have often been shown to exhibit overdispersion, which make it essential to use alternatives of Poisson to model such data. In this research, we apply the Poisson regression model and its alternatives in addition to the binary and ordered probit logistic regression model.
-
ESTIMATION OF MORTALITY RATES FOR THE GULF MENHADEN STOCK AND REFERENCE POINT IMPLEMENTATION FOR THE FISHERY
… natural mortality, catchability, and the overdispersion factor parameters. I established a Base model and n = 17 sensitivity models for robustness. I estimated a constant instantaneous natural mortality of 1.08 y<sup>-1</sup> with 95% confidence intervals of 1.04 y<sup>-1</sup> to 1.13 …
-
Examining uncertainty in environmental DNA analyses in freshwater lotic systems
… I also discuss the importance of accounting for overdispersion and non-detects that frequently arise in eDNA data due to the physical state of eDNA in aquatic environments. To my knowledge, this is the first eDNA experiment to directly examine eDNA quantification under a controlled, replicated …
-
Network meta-analysis with rare events and misclassified response.
… by accounting for both misclassification and overdispersion. Network meta-analysis is increasingly popular in clinical trials and provides both direct and indirect treatment comparisons. One common issue in network meta-analysis is zero outcomes, which will lead to biased estimates and low …
-
Sensory discrimination testing methodology selection based on beverage complexity
… of correct response, method power, and overdispersion were observed between methods when tested with the model beverage system. The findings from these studies emphasize the need for sensory professional to look beyond the categorization of methods by specified versus non-specified. …
-
The Effects of Geography, Environment and Phylogeny on Community Assembly and Gene Flow Dynamics
… across all spatial scales. Although leaf area overdispersion would be generally taken as evidence of competition, I argue that interpretation is probably misleading. Finally, I show that seedling survival is dramatically increased when they grow shaded by an adult individual, suggesting that …
-
The Censored Heterogeneous Negative Binomial Model
… binomial model involves a generalization of the overdispersion scale parameter, α, which allows for observation-specific parameterization of α. This form of the negative binomial model is known as the heterogeneous negative binomial model (HNB). </p> <p>This research explored the …
-
Modeling Crash Frequencies At Signalized Intersections In Central Flor
… Negative Binomial approach as the data showed overdispersion. The modeling process aimed to relate geometric and traffic factors to the frequency of crashes at intersections. Expected value analysis tables were also developed to determine if an intersection had an abnormally high number of …
-
Compositional models for mutational signature analysis
… than compositional models that do not allow any overdispersion. Similarly, the incorporation of random intercepts in the logistic-normal model for copy number data increases sensitivity with respect to the fixed-effects version. The models are publicly available on github and are readily …
-
Potential for using climate forecasts in spatio-temporal prediction of dengue fever incidence in Malaysia submitted
… successfully accounts for the large amount of overdispersion found in the observed dengue counts. Results indicated that there are statisti�cally significant relationships with both climate and non-climate covariates using this modelling framework. More specifically, smooth functions of year …
-
The Doubly Inflated Poisson and Related Regression Models
<p>Most real life count data consists of some values that are more frequent than allowed by the common parametric families of distributions. For data consisting of only excess zeros, in a seminal paper Lambert (1992) introduced Zero-Inflated Poisson (ZIP) model, which is a mixture model that …
Page 1 of 2