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Articles 1 - 8 of 8
Full-Text Articles in Physical Sciences and Mathematics
Optimal Clustering: Genetic Constrained K-Means And Linear Programming Algorithms, Jianmin Zhao
Optimal Clustering: Genetic Constrained K-Means And Linear Programming Algorithms, Jianmin Zhao
Theses and Dissertations
Methods for determining clusters of data under- specified constraints have recently gained popularity. Although general constraints may be used, we focus on clustering methods with the constraint of a minimal cluster size. In this dissertation, we propose two constrained k-means algorithms: Linear Programming Algorithm (LPA) and Genetic Constrained K-means Algorithm (GCKA). Linear Programming Algorithm modifies the k-means algorithm into a linear programming problem with constraints requiring that each cluster have m or more subjects. In order to achieve an acceptable clustering solution, we run the algorithm with a large number of random sets of initial seeds, and choose the solution …
Meta-Analysis Of Open Vs Closed Surgery Of Mandibular Condyle Fractures, Marcy Lauren Nussbaum
Meta-Analysis Of Open Vs Closed Surgery Of Mandibular Condyle Fractures, Marcy Lauren Nussbaum
Theses and Dissertations
A review of the literature reveals a difference of opinion regarding whether open or closed reduction of condylar fractures produces the best results. It would be beneficial to critically analyze past studies that have directly compared the two methods in an attempt to answer this question. A Medline search for articles using the key words 'mandibular condyle fractures' and 'mandibular condyle fractures surgery' was performed. The articles chosen for the meta-analysis contained data on at least one of the following: postoperative maximum mouth opening, lateral excursion, protrusion, deviation on opening, asymmetry, and joint pain or muscle pain. Several common statistical …
A Comparison For Longitudinal Data Missing Due To Truncation, Rong Liu
A Comparison For Longitudinal Data Missing Due To Truncation, Rong Liu
Theses and Dissertations
Many longitudinal clinical studies suffer from patient dropout. Often the dropout is nonignorable and the missing mechanism needs to be incorporated in the analysis. The methods handling missing data make various assumptions about the missing mechanism, and their utility in practice depends on whether these assumptions apply in a specific application. Ramakrishnan and Wang (2005) proposed a method (MDT) to handle nonignorable missing data, where missing is due to the observations exceeding an unobserved threshold. Assuming that the observations arise from a truncated normal distribution, they suggested an EM algorithm to simplify the estimation.In this dissertation the EM algorithm is …
A Normal-Mixture Model With Random-Effects For Rr-Interval Data, Jessica Mckinney Ketchum
A Normal-Mixture Model With Random-Effects For Rr-Interval Data, Jessica Mckinney Ketchum
Theses and Dissertations
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 exponential family, the case of the normal-mixture has not been dealt with adequately in the literature. The models and the estimation methods that have been proposed in the past assume the conditional model (fixing the random-effects) to be normal and allow a mixture distribution for the random effects (Xu and Hedeker, 2001, Xu, 1995). The methods proposed in this …
Quantifying The Effects Of Correlated Covariates On Variable Importance Estimates From Random Forests, Ryan Vincent Kimes
Quantifying The Effects Of Correlated Covariates On Variable Importance Estimates From Random Forests, Ryan Vincent Kimes
Theses and Dissertations
Recent advances in computing technology have lead to the development of algorithmic modeling techniques. These methods can be used to analyze data which are difficult to analyze using traditional statistical models. This study examined the effectiveness of variable importance estimates from the random forest algorithm in identifying the true predictor among a large number of candidate predictors. A simulation study was conducted using twenty different levels of association among the independent variables and seven different levels of association between the true predictor and the response. We conclude that the random forest method is an effective classification tool when the goals …
Statistical Methods And Experimental Design For Inference Regarding Dose And/Or Interaction Thresholds Along A Fixed-Ratio Ray, Sharon Dziuba Yeatts
Statistical Methods And Experimental Design For Inference Regarding Dose And/Or Interaction Thresholds Along A Fixed-Ratio Ray, Sharon Dziuba Yeatts
Theses and Dissertations
An alternative to the full factorial design, the ray design is appropriate for investigating a mixture of c chemicals, which are present according to a fixed mixing ratio, called the mixture ray. Using single chemical and mixture ray data, we can investigate interaction among the chemicals in a particular mixture. Statistical models have been used to describe the dose-response relationship of the single agents and the mixture; additivity is tested through the significance of model parameters associated with the coincidence of the additivity and mixture models.It is often assumed that a chemical or mixture must be administered above an unknown …
Design And Analysis Methods For Cluster Randomized Trials With Pair-Matching On Baseline Outcome: Reduction Of Treatment Effect Variance, Misook Park
Theses and Dissertations
Cluster randomized trials (CRT) are comparative studies designed to evaluate interventions where the unit of analysis and randomization is the cluster but the unit of observation is individuals within clusters. Typically such designs involve a limited number of clusters and thus the variation between clusters is left uncontrolled. Experimental designs and analysis strategies that minimize this variance are required. In this work we focus on the CRT with pre-post intervention measures. By incorporating the baseline measure into the analysis, we can effectively reduce the variance of the treatment effect. Well known methods such as adjustment for baseline as a covariate …
Assessing, Modifying, And Combining Data Fields From The Virginia Office Of The Chief Medical Examiner (Ocme) Dataset And The Virginia Department Of Forensic Science (Dfs) Datasets In Order To Compare Concentrations Of Selected Drugs, Amy Elizabeth Herrin
Theses and Dissertations
The Medical Examiner of Virginia (ME) dataset and the Virginia Department of Forensic Science Driving Under the Influence of Drugs (DUI) datasets were used to determine whether people have the potential to develop tolerances to diphenhydramine, cocaine, oxycodone, hydrocodone, methadone, and morphine. These datasets included the years 2000-2004 and were used to compare the concentrations of these six drugs between people who died from a drug-related cause of death (of the drug of interest) and people who were pulled over for driving under the influence. Three drug pattern groups were created to divide each of the six drug-specific datasets in …