Este trabalho visa estudar o modelo de Cox-Aalen, que incorpora efeitos fixos e variantes no tempo por meio das estruturas aditiva e multiplicativa. Os principais modelos aditivos e multiplicativos que englobam efeitos fixos e variantes no tempo são revisados com enfoque de processos de contagem e um teste do tipo escore para auxiliar na escolha entre a estrutura aditiva e multiplicativa é proposto e avaliado por meio de estudos de simulação. Aplicação e comparação dos principais modelos discutidos em dados do Instituto do Câncer do Estado de São Paulo (ICESP) sugerem que o modelo estudado pode ser uma opção interessante na análise de dados de sobrevivência em que as ferramentas usuais não são adequadas. / This dissertation aims to study the Cox-Aalen regression model, which incorporates fixed and time-varying effects through the additive and multiplicative structures. The primary additive and multiplicative risk models that deal with fixed and time-dependent effects are reviewed with the counting process framework and a score test to assist the decision between the additive and multiplicative structures is proposed and evaluated with a simulation study. The application of the models to the Instituto do Câncer do Estado de São Paulo (ICESP) dataset suggests that the model under study can be considered as an interesting option to analyse survival data when the usual techniques are not aproppriate.

The statistical practice of equating is needed when scores on different versions of the same standardized test are to be compared. This thesis constitutes four contributions to the observed-score equating framework kernel equating. Paper I introduces the open source R package kequate which enables the equating of observed scores using the kernel method of test equating in all common equating designs. The package is designed for ease of use and integrates well with other packages. The equating methods non-equivalent groups with covariates and item response theory observed-score kernel equating are currently not available in any other software package. In paper II an alternative bandwidth selection method for the kernel method of test equating is proposed. The new method is designed for usage with non-smooth data such as when using the observed data directly, without pre-smoothing. In previously used bandwidth selection methods, the variability from the bandwidth selection was disregarded when calculating the asymptotic standard errors. Here, the bandwidth selection is accounted for and updated asymptotic standard error derivations are provided. Item response theory observed-score kernel equating for the non-equivalent groups with anchor test design is introduced in paper III. Multivariate observed-score kernel equating functions are defined and their asymptotic covariance matrices are derived. An empirical example in the form of a standardized achievement test is used and the item response theory methods are compared to previously used log-linear methods. In paper IV, Wald tests for equating differences in item response theory observed-score kernel equating are conducted using the results from paper III. Simulations are performed to evaluate the empirical significance level and power under different settings, showing that the Wald test is more powerful than the Hommel multiple hypothesis testing method. Data from a psychometric licensure test and a standardized achievement test are used to exemplify the hypothesis testing procedure. The results show that using the Wald test can provide different conclusions to using the Hommel procedure.

Este trabalho visa estudar o modelo de Cox-Aalen, que incorpora efeitos fixos e variantes no tempo por meio das estruturas aditiva e multiplicativa. Os principais modelos aditivos e multiplicativos que englobam efeitos fixos e variantes no tempo são revisados com enfoque de processos de contagem e um teste do tipo escore para auxiliar na escolha entre a estrutura aditiva e multiplicativa é proposto e avaliado por meio de estudos de simulação. Aplicação e comparação dos principais modelos discutidos em dados do Instituto do Câncer do Estado de São Paulo (ICESP) sugerem que o modelo estudado pode ser uma opção interessante na análise de dados de sobrevivência em que as ferramentas usuais não são adequadas. / This dissertation aims to study the Cox-Aalen regression model, which incorporates fixed and time-varying effects through the additive and multiplicative structures. The primary additive and multiplicative risk models that deal with fixed and time-dependent effects are reviewed with the counting process framework and a score test to assist the decision between the additive and multiplicative structures is proposed and evaluated with a simulation study. The application of the models to the Instituto do Câncer do Estado de São Paulo (ICESP) dataset suggests that the model under study can be considered as an interesting option to analyse survival data when the usual techniques are not aproppriate.

<p>Our primary goal is to better understand complex diseases using statistically disciplined approaches. As multi-modal data is streaming out of consortium projects like Genotype-Tissue Expression (GTEx) project, which aims at collecting samples from various tissue sites in order to understand tissue-specific gene regulation, new approaches are needed that can efficiently model groups of data with minimal loss of power. For example, GTEx project delivers RNA-Seq, Microarray gene expression and genotype data (SNP Arrays) from a vast number of tissues in a given individual subject. In order to analyze this type of multi-level (hierarchical) multi-modal data, we proposed a series of efficient-score based tests or score tests and leveraged groups of tissues or gene isoforms in order map genomic biomarkers. We model group-specific variability as a random effect within a mixed effects model framework. In one instance, we proposed a score-test based approach to map expression quantitative trait loci (eQTL) across multiple-tissues. In order to do that we jointly model all the tissues and make use of all the information available to maximize the power of eQTL mapping and investigate an overall shift in the gene expression combined with tissue-specific effects due to genetic variants. In the second instance, we showed the flexibility of our model framework by expanding it to include tissue-specific epigenetic data (DNA methylation) and map eQTL by leveraging both tissues and methylation. Finally, we also showed that our methods are applicable on different data type such as whole transcriptome expression data, which is designed to analyze genomic events such alternative gene splicing. In order to accomplish this, we proposed two different models that exploit gene expression data of all available gene-isoforms within a gene to map biomarkers of interest (either genes or gene-sets) in paired early-stage breast tumor samples before and after treatment with external beam radiation. Our efficient score-based approaches have very distinct advantages. They have a computational edge over existing methods because they do not need parameter estimation under the alternative hypothesis. As a result, model parameters only have to be estimated once per genome, significantly decreasing computation time. Also, the efficient score is the locally most powerful test and is guaranteed a theoretical optimality over all other approaches in a neighborhood of the null hypothesis. This theoretical performance is born out in extensive simulation studies which show that our approaches consistently outperform existing methods both in statistical power and computational speed. We applied our methods to publicly available datasets. It is important to note that all of our methods also accommodate the analysis of next-generation sequencing data.</p> / Dissertation

Submitted by (ana.araujo@ufrpe.br) on 2016-07-07T14:09:13Z No. of bitstreams: 1 Katia Pires do Nascimento.pdf: 303593 bytes, checksum: 6b936f81d2b21d770e2224c3fbdd07c1 (MD5) / Made available in DSpace on 2016-07-07T14:09:13Z (GMT). No. of bitstreams: 1 Katia Pires do Nascimento.pdf: 303593 bytes, checksum: 6b936f81d2b21d770e2224c3fbdd07c1 (MD5) Previous issue date: 2010-02-25 / This manuscript has two aims. First, we derive general matrix formulae to Bartlett–type correction to the score statistic in a class of heteroscedastic symmetric nonlinear regression models, with link functions any for both mean and dispersion parameter. In the second part Monte Carlo simulations are also performed to assess the influence of the correction in the models studied. / Essa dissertação tem dois objetivos. O primeiro é a obtenção de expressões matriciais para o fator de correção tipo–Bartlett para a estatística escore nos modelos não–lineares simétricos heteroscedásticos, com funções de ligação quaisquer para a média e para o parâmetro de dispersão. O segundo é apresentar resultados de simulação de forma a verificar a influência da correção nos modelos em estudo.

This paper deals with possibilities and functions of modern graphic accelerators and with measuring performance under OpenGL interface. Widespread algorithms to render scene in real-time are used. It focuses on how to test every part of accelerator's graphic pipeline as well as measure performance in rendering of advanced effects and theoretical speed at general purpose calculations through graphic processor. This testing is realized by implementing multiple test series and their further evaluation. Final application enables setting of test parameters and outputs a score, by which is possible to judge accelerator's performance in comparison among themselves.

Le but de ce travail a été de proposer des méthodes d'inférence pour décrire l'histoire naturelle de la phase pré-diagnostic de la démence. Durant celle-ci, qui dure une quinzaine d'années, les trajectoires de déclin cognitif sont non linéaires et hétérogènes entre les sujets. Pour ces raisons, nous avons choisi un modèle à changement de pente aléatoire pour les décrire. Une première partie de ce travail a consisté à proposer une procédure de test pour l'existence d'un changement de pente aléatoire. En effet, dans certaines sous-populations, le déclin cognitif semble lisse et la question de l'existence même d'un changement de pente se pose. Cette question présente un défi méthodologique en raison de la non-identifiabilité de certains paramètres sous l'hypothèse nulle rendant les tests standards inutiles. Nous avons proposé un supremum score test pour répondre à cette question. Une seconde partie du travail concernait l'ordre temporel du temps de changement entre plusieurs marqueurs. La démence est une maladie multidimensionnelle et plusieurs dimensions de la cognition sont affectées. Des schémas hypothétiques existent pour décrire l'histoire naturelle de la démence mais n'ont pas été éprouvés sur données réelles. Comparer le temps de changement de différents marqueurs mesurant différentes fonctions cognitives permet d'éclairer ces hypothèses. Dans cet esprit, nous proposons un modèle bivarié à changement de pente aléatoire permettant de comparer les temps de changement de deux marqueurs, potentiellement non gaussiens. Les méthodes proposées ont été évaluées sur simulations et appliquées sur des données issues de deux cohortes françaises. Enfin, nous discutons les limites de ces deux modèles qui se concentrent sur une accélération tardive du déclin cognitif précédant le diagnostic de démence et nous proposons un modèle alternatif qui estime plutôt une date de décrochage entre cas et non-cas. / The aim of this work was to propose inferential methods to describe natural history of the pre-diagnosis phase of dementia. During this phase, which can last around fifteen years, the cognitive decline trajectories are nonlinear and heterogeneous between subjects. Because heterogeneity and nonlinearity, we chose a random changepoint mixed model to describe these trajectories. A first part of this work was to propose a testing procedure to assess the existence of a random changepoint. Indeed, in some subpopulations, the cognitive decline seems smooth and the question of the existence of a changepoint itself araises. This question is methodologically challenging because of identifiability issues on some parameters under the null hypothesis that makes standard tests useless. We proposed a supremum score test to answer this question. A second part of this work was the comparison of the temporal order of different markers changepoint. Dementia is a multidimensional disease where different dimensions of the cognition are affected. Hypothetic cascade models exist for describing this natural history but have not been evaluated on real data. Comparing change over time of different markers measuring different cognitive functions gives precious insight on this hypothesis. In this spirit, we propose a bivariate random changepoint model allowing proper comparison of the time of change of two cognitive markers, potentially non Gaussian. The proposed methodologies were evaluated on simulation studies and applied on real data from two French cohorts. Finally, we discussed the limitations of the two models we used that focused on the late acceleration of the cognitive decline before dementia diagnosis and we proposed an alternative model that estimates the time of differentiation between cases and non-cases.

No description available.

This thesis investigates the factors that are associated with annual changes in the share price of Johannesburg Stock Exchange (JSE) listed companies. In this study, an increase in value of a share is when the share price of a company goes up by the end of the financial year as compared to the previous year. Secondary data that was sourced from McGregor BFA website was used. The data was from 2004 up to 2011. Deciding which share to buy is the biggest challenge faced by both investment companies and individuals when investing on the stock exchange. This thesis uses binary logistic regression to identify the variables that are associated with share price increase. The dependent variable was annual change in share price (ACSP) and the independent variables were assets per capital employed ratio, debt per assets ratio, debt per equity ratio, dividend yield, earnings per share, earnings yield, operating profit margin, price earnings ratio, return on assets, return on equity and return on capital employed. Different variable selection methods were used and it was established that the backward elimination method produced the best model. It was established that the probability of success of a share is higher if the shareholders are anticipating a higher return on capital employed, and high earnings/ share. It was however, noted that the share price is negatively impacted by dividend yield and earnings yield. Since the odds of an increase in share price is higher if there is a higher return on capital employed and high earning per share, investors and investment companies are encouraged to choose companies with high earnings per share and the best returns on capital employed. The final model had a classification rate of 68.3% and the validation sample produced a classification rate of 65.2% / Mathematical Sciences / M.Sc. (Statistics)

Neste trabalho, desenvolvemos três tópicos relacionados a modelos de regressão da família exponencial. No primeiro tópico, obtivemos a matriz de covariância assintótica de ordem $n^$, onde $n$ é o tamanho da amostra, dos estimadores de máxima verossimilhança corrigidos pelo viés de ordem $n^$ em modelos lineares generalizados, considerando o parâmetro de precisão conhecido. No segundo tópico calculamos o coeficiente de assimetria assintótico de ordem n^{-1/2} para a distribuição dos estimadores de máxima verossimilhança dos parâmetros que modelam a média e dos parâmetros de precisão e dispersão em modelos não-lineares da família exponencial, considerando o parâmetro de dispersão desconhecido, porém o mesmo para todas as observações. Finalmente, obtivemos fatores de correção tipo-Bartlett para o teste escore em modelos não-lineares da família exponencial, considerando covariáveis para modelar o parâmetro de dispersão. Avaliamos os resultados obtidos nos três tópicos desenvolvidos por meio de estudos de simulação de Monte Carlo / In this work, we develop three topics related to the exponential family nonlinear regression. First, we obtain the asymptotic covariance matrix of order $n^$, where $n$ is the sample size, for the maximum likelihood estimators corrected by the bias of order $n^$ in generalized linear models, considering the precision parameter known. Second, we calculate an asymptotic formula of order $n^{-1/2}$ for the skewness of the distribution of the maximum likelihood estimators of the mean parameters and of the precision and dispersion parameters in exponential family nonlinear models considering that the dispersion parameter is the same although unknown for all observations. Finally, we obtain Bartlett-type correction factors for the score test in exponential family nonlinear models assuming that the precision parameter is modelled by covariates. Monte Carlo simulation studies are developed to evaluate the results obtained in the three topics.