Thesis (M.S.)--Worcester Polytechnic Institute. / Keywords: FDR; logistic regression; microarray. Includes bibliographical references (leaf 26).

Theses (Ed. D.)--Marshall University, 2005. / Title from document title page. Includes abstract. Document formatted into pages: contains ix, 180 p. Bibliography: p. 121-129.

Thesis (Ph. D.)--Florida State University, 2006. / Advisor: Daniel L. McGee, Sr., Florida State University, College of Arts and Sciences, Dept. of Statistics. Title and description from dissertation home page (viewed Sept. 21, 2006). Document formatted into pages; contains xii, 147 pages. Includes bibliographical references.

Variable selection refers to the problem of selecting input variables that are most predictive of a given outcome. Variable selection problems are found in all machine learning tasks, supervised or unsupervised, classification, regression, time series prediction , two - class or multi-class, posing various levels of challenges. Variables selection problems are related to the problems of input dimensionality reduction and of parameter planning. It has practical and theoretical challenges of its own. From the practical point of view, eliminating variables may reduce the cost of producing the outcome and increase its speed, while space dimensionality does not address these problems. Theoretical challenges include estimating with what confidence one can state that a variable is relevant to the concept when it is useful to the outcome and providing a theoretical understanding of the stability of selected variables subsets. As the probability cut-points increase in value, the more likely it becomes that an observation is classified as a non-event by the selected variables. The mathematical statement of the problem is not widely agreed upon and may depend on the application. One typically distinguishes: i) The problem of discovering all the variables relevant to the outcome variable and determine HOW relevant they are and how they are related to each other. ii) The problem of finding a minimum subset of variables that is useful to the outcome variable. Logistic regression is an increasingly popular statistical technique used to model the probability of discrete binary outcome. Logistic regression applies maximum likelihood estimation after transforming the outcome variable into a logit variable. In this way, logistic regression estimates the probability of a certain event. When properly applied, logistic regression analyses yield a very powerful insight in to what variables are more or less likely to predict event outcome in a population of interest. These models also show the extent to which changes in the values of the variable may increase or decrease the predicted probability of event outcome. Variable selection, in all its facets is similarly important with logistic regression. The receiver operating characteristics (ROC) curve is a graphic display that gives a measure of the predictive accuracy of a logistic regression model. It is a measure of classification performance, the area under the ROC curve (AUC) is a scalar measure gauging one facet of performance. Another measure of predictive accuracy of a logistic regression model is a classification table. It uses the model to classifying observations as events if their estimated probability is greater or equal to a given probability cut-point, otherwise events are classified as non-events. This technique, as it appears in the literature, is also studied in this thesis. In this thesis the issue of variable selection, both for continuous and binary outcome variables, is investigated as it appears in the statistical literature. It is clear that this topic has been widely researched and still remains a feature of modern research. The last word certainly hasn’t been spoken. / Dissertation (MSc)--University of Pretoria, 2008. / Statistics / unrestricted

The Appalachian Mountains in eastern Tennessee are known for landslides, and landslides are reported to cause millions of dollars of damage. To aid in the estimation of future susceptibility, geographic information systems was used to perform a logistic regression, to identify landslides in eastern Tennessee. Landslide model results validated using Kold cross validation. The model results suggest that the environmental variables slope, soil, landcover/vegetation, and distance to roads were significant factors related to landslide susceptibility. The susceptibility map showed that 86.8% of urban areas in eastern Tennessee were at highest susceptibility for landslides, possibly due to lower amounts of landcover. By overlaying past landslides on landslide susceptibility for accuracy, areas with high landslide susceptibility were found in areas along main highways and interstates. This model is a first step in using GIS to increase the awareness of landslide susceptibility in the regions and may ultimately lead to better preparation.

An ongoing debate in society is about the existence of a wage gap between genders, and society’s alleged preference to hire a man over an equally qualified woman. This debate extends from the commercial employment world into the funding of research grants. Given data collected at North Dakota State University between 2012 and 2018 have women who have sought federal funding for their research experienced a gender bias? To investigate, a logistic regression model is fit to determine whether gender affects funding probability. Other characteristics such as the primary investigator’s college, requested amount, and the research team’s make up of tenured and Caucasian members is also investigated. It was found that there is not a gender bias towards faculty at NDSU. Naturally, there was a bias towards researchers from different colleges and towards proposals requesting less funding. Surprisingly, a bias towards higher-proportion Caucasian research projects was found.

Graduate student persistence rarely has been studied, yet it is a very important issue for many higher education constituents—including senior administrators, academic deans, faculty members, students, and families. In light of an alarming statistic that approximately 50% of all graduate students fail to complete their degree, there have been few studies to examine this phenomenon and no new models to explain the relationship between factors that influence graduate student persistence. This dissertation examined persistence by graduate students to degree using data from the National Center for Education Statistics' Baccalaureate and Beyond (B&B:93/97) Longitudinal Survey. First, I proposed a logical model of graduate student persistence using economic, academic, and non-academic variables. Then, I tested the model's ability to predict graduate student persistence to degree. Analyses were conducted to answer the following questions: 1. Does more than money matter in predicting graduate student persistence? 2. To what extent do economic, academic and non-academic factors included in the integrated model predict graduate student persistence? a) Does this differ by graduate student status (e.g., master's and doctoral)? If so, how? 3. Using the integrated model, does the likelihood of persisting in graduate school vary by race/ethnicity? If so, how? a) How do student aid and undergraduate debt influence the observed racial/ethnic group differences in persistence? The results of this study suggest that more than money matters when predicting graduate student persistence. The integrate model of graduate student persistence, developed for this study, is statistically significantly better at predicting graduate student persistence than a model that only includes economic factors. The integrated model tested to be most fit for predicting persistence among doctoral students. And, finally, using the model, the likelihood of persisting in graduate school varies by race/ethnicity. Student aid tends to improve one's chances of persisting in graduate school while undergraduate debt is associated with failing to persist in graduate school. / Ph. D.

O conceito de logística vem, ao longo do tempo, agregando novos elementos e tornando-se mais complexo. Nos anos 50 restringia-se à distribuição física. Atualmente engloba a totalidade dos fluxos de material, produtos e informação entre diferentes empresas da cadeia de suprimentos. Neste contexto, organizações dos mais variados segmentos vêm terceirizando suas operações logísticas para empresas especializadas denominadas operadores logísticos. As tecnologias de informação (TI) têm um importante papel no desenvolvimento das atividades logísticas e no desempenho dos operadores: suas aplicações permitem a otimização do sistema logístico e o gerenciamento de forma integrada de seus diversos componentes. O objetivo da pesquisa é investigar como a TI vem sendo utilizada pelos operadores nos processos logísticos e como vem contribuindo para o estabelecimento de redes de valor. A metodologia utilizada foi o estudo de casos múltiplos. Foram investigados cinco operadores logísticos com atuação no mercado brasileiro, com diferentes posicionamentos estratégicos, operando em diferentes setores e de modo a cobrir de forma integral o processo logístico. Os resultados da pesquisa indicaram a necessidade do desenvolvimento de aplicativos customizados, capazes de atender as particularidades de cada operador e de gerar vantagens competitivas, e apontaram a importância do papel da TI para o estabelecimento das redes de valor. / The logistics concept has been changing, adding new elements and becoming more complex. In the fifties it was restricted to physical distribution only. Nowadays, it embraces the total flow of materials, products and information between the different companies of a supply chain. In this new scenario, organizations in all industries have outsourced their logistics operations to specialized companies called logistics operators. Information technologies (IT) have an important role in the development of logistics activities and in the logistics operator\'s performance: IT applications allow an optimal tuning of the logistics system and an integrated management of its several components. The purpose of this research is to investigate how the logistics operators are applying IT in the logistics process and how IT is contributing to the establishment of value networks. The methodology utilized was the multiple cases study. Five logistic operators that feature different strategic positions and operate with different industries in the Brazilian market were investigated. The sample was chosen so as to provide the information needed for an analysis of all stages of the logistic process. The results of the research indicate that customized applications, suited to the particularities of each operator, play an important role in the creation of competitive advantages, and suggest the centrality of IT in the creation of value networks.

O conceito de logística vem, ao longo do tempo, agregando novos elementos e tornando-se mais complexo. Nos anos 50 restringia-se à distribuição física. Atualmente engloba a totalidade dos fluxos de material, produtos e informação entre diferentes empresas da cadeia de suprimentos. Neste contexto, organizações dos mais variados segmentos vêm terceirizando suas operações logísticas para empresas especializadas denominadas operadores logísticos. As tecnologias de informação (TI) têm um importante papel no desenvolvimento das atividades logísticas e no desempenho dos operadores: suas aplicações permitem a otimização do sistema logístico e o gerenciamento de forma integrada de seus diversos componentes. O objetivo da pesquisa é investigar como a TI vem sendo utilizada pelos operadores nos processos logísticos e como vem contribuindo para o estabelecimento de redes de valor. A metodologia utilizada foi o estudo de casos múltiplos. Foram investigados cinco operadores logísticos com atuação no mercado brasileiro, com diferentes posicionamentos estratégicos, operando em diferentes setores e de modo a cobrir de forma integral o processo logístico. Os resultados da pesquisa indicaram a necessidade do desenvolvimento de aplicativos customizados, capazes de atender as particularidades de cada operador e de gerar vantagens competitivas, e apontaram a importância do papel da TI para o estabelecimento das redes de valor. / The logistics concept has been changing, adding new elements and becoming more complex. In the fifties it was restricted to physical distribution only. Nowadays, it embraces the total flow of materials, products and information between the different companies of a supply chain. In this new scenario, organizations in all industries have outsourced their logistics operations to specialized companies called logistics operators. Information technologies (IT) have an important role in the development of logistics activities and in the logistics operator\'s performance: IT applications allow an optimal tuning of the logistics system and an integrated management of its several components. The purpose of this research is to investigate how the logistics operators are applying IT in the logistics process and how IT is contributing to the establishment of value networks. The methodology utilized was the multiple cases study. Five logistic operators that feature different strategic positions and operate with different industries in the Brazilian market were investigated. The sample was chosen so as to provide the information needed for an analysis of all stages of the logistic process. The results of the research indicate that customized applications, suited to the particularities of each operator, play an important role in the creation of competitive advantages, and suggest the centrality of IT in the creation of value networks.

The dissertation deals with parameters of logistic processes structure in a manufacturing company. The logistic processes structure in a manufacturing company means the logistic processes and their relationships in a manufacturing company. The main objective of the thesis is to create an overview of parameters of the logistic processes structure in manufacturing companies. Cognition and formation of the logistic processes structure is important for planning, control and management of elements of the logistic chain. The thesis focuses on the logistic processes structure in a manufacturing company and the examination of their instantiations. To achieve the objective, in the thesis it was necessary to propose a unifying classification of logistic processes, as well as the general classification for the integration of logistic functions in the organization of a manufacturing company. The proposed classifications and proposed parameters allowed to compare the results of research concerning the comparison of different logistic processes (or operations) in companies.