The objective of this research study is to explore trajectories of health-related quality of life (HRQoL) in older breast cancer survivors, along with their predictors. HRQoL is important because patients who show severe symptoms may wish to consider therapies or treatment plans that lead to better HRQoL. Older people are more vulnerable to low HRQoL scores since old age is associated with deteriorating health, multiple comorbidities, and low-socioeconomic status. To examine the HRQoL trajectory among older women with breast cancer, we used the data queried from the Surveillance, Epidemiology and End Results Medicare Health Outcomes Survey database. A total of 1,089 older (≥ 65 years) women who were diagnosed with breast cancer in 1998-2012 and participated in the survey before and after the cancer diagnosis were identified. HRQoL was measured using SF-36/VR-12 questionnaire and summarized as Physical Component Summary (PCS) Score and Mental Component Summary (MCS) Score. Latent Class Growth Mixture Modeling was conducted to identify distinct groups of women with a similar trajectory of HRQoL. The results showed that there were three latent classes of HRQoL trajectories for PCS: the high-declining (46.5% of the sample), mid-declining (36.0%), and the low-improving (17.5%). Two latent classes of HRQoL trajectories were identified for MCS: high-stable (76.5%) and low-declining (23.5%). The results showed that age at diagnosis, BMI, level of education, geographic region, tumor grade, tumor size, and number of comorbidities were some of the major predictors of health-related quality of life. These predictors were further explored using multinomial logistic regression analysis which identified number of comorbidities as the most significant predictor for HRQoL-PCS scores and level of education as the most significant predictor for HRQoL-MCS scores. This suggests that future research needs to be conducted, identifying the most common comorbidities in older breast cancer survivors to develop interventions that better the physical HRQoL in patients, in addition to the development of mental HRQoL interventions for patients that are less educated.

No description available.

In 1993, a travel study was conducted along the Wasatch front in Utah (Research Systems Group INC, 2013). The main purpose of this study was to assess travel behavior to understand the needs for future growth in Utah. Since then, the Research Service Group (RSG), conducted a new study in 2012 to understand current travel preferences in Utah. This survey, called the Residential Choice Stated Preference survey, asked respondents to make ten choice comparisons between two hypothetical homes. Each home in the choice comparison was described by different attributes, those attributes that were used are, type of neighborhood, distance from important destinations, distance from access to public transport, street design, parking availability, commute distance to work, and price. The survey was designed to determine the extent to which Utah residents prefer alternative household attributes in a choice selection. Each attribute contained multiple characteristic levels that were randomly combined to define each alternative home in each choice comparison. Those choices can be explained by Random Utility Theory. Multinomial logistic regression will be used to estimate changes in utility when alternative attribute levels are present in a choice comparison. Using the coefficient estimate for price, a marginal willingness to pay (MWTP) for each attribute level will be calculated. This paper will use two different approaches to obtain MWTP estimates. Method One will use housing and rent price to recode the price variable in dollar terms as defined in the discrete choice experiment. Method Two will recode the price variable as an average ten percent change in home value to extrapolate a one-time payment for homes. As a result, we found that it is possible to obtain willingness to pay estimates using both methods. The resulting interpretations in dollar terms became more relatable. Metropolitan planning organization can use these results to understand how residents perceive home value in dollar terms in the context of location-based attributes for homes.

Every day most people are using applications and services that are utilising machine learning, in some way, without even knowing it. Some of these applications and services could, for example, be Google’s search engine, Netflix’s recommendations, or Spotify’s music tips. For machine learning to work it needs data, and often a large amount of it. Roughly 2,5 quintillion bytes of data are created every day in the modern information society. This huge amount of data can be utilised to make applications and systems smarter and automated. Time logging systems today are usually not smart since users of these systems still must enter data manually. This bachelor thesis will explore the possibility of applying machine learning to task logging systems, to make it smarter and automated. The machine learning algorithm that is used to predict the user’s task, is called multiclass logistic regression, which is categorical. When a small amount of training data was used in the machine learning process the predictions of a task had a success rate of about 91%.

Made available in DSpace on 2016-08-02T21:42:51Z (GMT). No. of bitstreams: 1 Renato Capa.pdf: 2822964 bytes, checksum: 9f2246d51556a8c6fc6872b40ebdd02c (MD5) Previous issue date: 2008-08-13 / The main objective of this study is to analyze the determinants of the composition the board of directors in small and medium private owned publicly traded companies in the region of ABC paulista. The study is motivated by the reason that in Brazil there is little or no studies approaching this subject and the studies presented abroad on analyzing the size board, the types of directories, the financial performance, the independence, etc., of the companies and none of them had its focus in composition the board of directors in small and medium private owned publicly traded companies. In the light of above, the current research is scheduled to try to find out an answer to the following questions: What factors were determinant to establish the composition of the board of directors in small medium private owned publicly traded companies of the region of ABC paulista? From this problem statement we established to the following hypotheses: If the power and the influence of CEO/Chairman of the board in companies of small and medium size is high, there will be possibilities to have external advisers; Should there be clear segregation of function between the CEO and the Chairman of the board and if the CEO would be interested to preserve his act and mandate then there will be a possibility to have internal advisers; Should there be interest in the efficiency, performance of the company, then there will be a possibility to have external advisers; Should the company be in the circle of expansion and maturity, then there will be a possibility to adopt and to have external advisers.(AU) / O principal objetivo deste estudo é analisar os determinantes de composição de Conselho de Administração em pequenas e médias empresas de sociedade anônima de capital fechado da região do ABC paulista. A razão de iniciar este trabalho, surgiu devido à constatação de que no Brasil existem poucos artigos e dissertações que tratam de composição de Conselho e os elaborados no exterior se centralizaram na composição em termos de tamanho e tipos de diretores, de desempenho financeiro, de independência etc., mas nenhum deles focou nas determinantes de composição de pequena e média empresa. Portanto, baseando-se nas observações acima, se efetuou pesquisa de campo para responder à seguinte problemática Que determinante(s) estabelece(m) a composição de Conselho de Administração de Pequenas e Médias Empresas de Sociedade Anônima de Empresas da Região do ABC paulista? Partindo dessa problemática, se estabeleceu as seguintes hipóteses: se o poder e a influência do CEO/Presidente do Conselho em empresas de pequeno e médio porte são grandes, então existem baixas possibilidades de ter Conselheiros Externos; se houver segregação de cargos entre o CEO e o Presidente do Conselho e o CEO estiver interessado em preservar a sua atuação, então há probabilidade de escolher Conselheiros Internos; se houver segregação de cargos entre o CEO e o Presidente do Conselho e o CEO estiver interessado na eficiência, orientação e na necessidade de recursos externos, então há probabilidade de escolher Conselheiros Externos; se a empresa está no Ciclo de Vida Expansão e Maturidade- , então há possibilidades de adotarem Conselheiros Externos.(AU)

The thesis deals with a mortality modelling in the Czech Republic. The main aim of this thesis is to describe historical development of mortality in the Czech Republic on the basis of multinomial regression. In a theoretical part the basic knowledge demanded for model construction divided into two chapters can be found. In the first chapter the basic difference between linear and generalized linear model is described. Second chapter is devoted to a logistic regression. Here we proceed from simple, binomial variable and then we generalize it for multinomial variable. Practical part deals with a construction of a described model. In the third chapter data (type and source) are described and in the fourth chapter characterizes all three models itself (two of them are descriptive and the third one is used for simple prediction). The prediction is added rather for completeness than for the importance of the work itself because it was not the main goal.

Das Verkehrsmittelwahlverhalten von Menschen ist komplex. So spielen soziodemografische, sozioökonomische sowie raum- und siedlungsstrukturelle Merkmale eine Rolle. In dieser Arbeit wird dieses Verhalten untersucht. Dabei wird eine homogene Grundgesamtheit geschaffen, welche alle Personen beinhaltet, die sowohl über eine Dauerkarte des öffentlichen Personenverkehrs als auch einen Personenkraftwagen verfügen. Anhand derer soll eine deskriptive Analyse und eine multinomiale logistische Regression Aufschluss geben, ob es Unterschiede zwischen den jeweiligen Nutzergruppen gibt. So lässt sich die Gruppe der ÖV-Nutzer durch folgende Charakteristiken beschreiben: der Großteil sind Frauen, sowie Personen, die eine hohe schulische und berufliche Bildung besitzen. Des Weiteren werden eher weniger Wege mit dem ÖV als mit dem PKW zurückgelegt. Erwerbstätige hingegen entscheiden sich eher für den PKW. / Human behavior towards the choice of transportation varies in very complex ways such as sociodemographics, socioeconomics as well as settlement structures. For this paper a homogenous population is created from season ticket holders for public transportation and car owners. Based on this population a descriptive analysis followed by a multinomial logistic regression is supposed to generate the differences between the user groups. The group of users of the public transportation system can be characterized as followed: the majority of users are women as well as highly educated people. Within this specific group distances are more likely to be covered by public transportation rather than by car. However the working population prefers to go by passenger car.

No description available.

Studien undersöker vilken modell som bäst modellerar matchutfallet (1,X,2 - Hemmavinst, Oavgjort, Bortavinst) på en fotbollsmatch utifrån matchstatistik. Datan som analyserats är sammanställd från den engelska fotbollens tre högsta divisioner från 2005 och framåt. Multinomial logistisk regression tillämpas för att modellera responsvariabeln utifrån förklaringsvariablerna. Med hjälp av best subset regression undersöks alla kombinationer av variabler och modellerna jämförs utifrån Akaike Information Criterion (AIC). Tillsammans med resultatet från regressionerna och en analys över multikollinearitet väljs den bästa modellen.  Resultatet visar på både väntade och oväntade effekter vilket skapar grund för framtida studier. Förbättringsområden för framtida studier innefattar fler förklaringsvariabler, jämförelser med spelbolagens odds och test på ny testdata. Tillämpningsområden för modellen är inom spelbranschen där modellen kan användas för att värdera kombinationsspel och liveodds. / This study aims to find the best model to predict the outcome of football (1,X,2 - Home Win, Draw, Away Win) games by looking at match data. The data used is put together from the three highest football divisions in England and go back to the year 2005. Multinomial logistic regression is used to model the response variable from the regressors. A best subset regression is used to find the models with the lowest Akaike Information Criterion (AIC). By doing a multicollinearity analysis these models are further examined and the best one is chosen.  The results show both expected and unexpected effects that create foundation for future studies. Areas for model improvement include more variables, comparison with the bookmaker’s odds and tests on new test data. The application of the model is in sports betting where it can be used to value multi bets and live odds.

Dans ce mémoire, nous proposons une méthodologie statistique permettant d’obtenir un estimateur de l’espérance de vie des clients en assurance. Les prédictions effectuées tiennent compte des caractéristiques individuelles des clients, notamment du fait qu’ils peuvent détenir différents types de produits d’assurance (automobile, résidentielle ou les deux). Trois approches sont comparées. La première approche est le modèle de Markov simple, qui suppose à la fois l’homogénéité et la stationnarité des probabilités de transition. L’autre modèle – qui a été implémenté par deux approches, soit une approche directe et une approche par simulations – tient compte de l’hétérogénéité des probabilités de transition, ce qui permet d’effectuer des prédictions qui évoluent avec les caractéristiques des individus dans le temps. Les probabilités de transition de ce modèle sont estimées par des régressions logistiques multinomiales. / In this master’s thesis, we develop a statistical method to estimate the lifetime expectancy of clients in the insurance domain. The forecasts are personnalized according to the clients’ own features, the most notable being the fact that they can have any combination of automobile and residential insurance products. Three approaches are compared. The first approach is the simple Markov model which assume homogeneity and stationnarity of the transition probabilities. The other model suggested – which is implemented both by direct computation and by simulation – allows for heterogeneity of the transition probabilities, thus providing forecasts which evolve in time along with the characteristics of the clients. The transitions probabilities are estimated using multinomial logistic regressions.