990 resultados para Local Partial Likelihood


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Experimental autoimmune encephalomyelitis (EAE) is an artificially induced demyelination of the central nervous system (CNS) that resembles multiple sclerosis in its clinical, histopathological, and immunological features. Activated Th1 and Th17 cells are thought to be the main immunological players during EAE development. This study was designed to evaluate peripheral and local contribution of IL-17 to acute and chronic EAE stages. C57BL/6 mice were immunized with MOG plus complete Freund's adjuvant followed by pertussis toxin. Mice presented an initial acute phase characterized by accentuated weight loss and high clinical score, followed by a partial recovery when the animals reached normal body weight and smaller clinical scores. Spleen cells stimulated with MOG produced significantly higher levels of IFN-γ during the acute period whereas similar IL-17 levels were produced during both disease stages. CNS-infiltrating cells stimulated with MOG produced similar amounts of IFN-γ but, IL-17 was produced only at the acute phase of EAE. The percentage of Foxp3+ Treg cells, at the spleen and CNS, was elevated during both phases. The degree of inflammation was similar at both disease stages. Partial clinical recovery observed during chronic EAE was associated with no IL-17 production and presence of Foxp3+ Treg cells in the CNS. © 2013 Sofia Fernanda Gonçalves Zorzella-Pezavento et al.

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Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

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Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

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In this paper, we show that the equation delta u/delta (z) over bar + Gu = f, where the elements involved are in generalized functions context, has a local solution in the generalized functions context.

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Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

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This paper examines the local power of the likelihood ratio, Wald, score and gradient tests under the presence of a scalar parameter, phi say, that is orthogonal to the remaining parameters. We show that some of the coefficients that define the local powers remain unchanged regardless of whether phi is known or needs to be estimated, where as the others can be written as the sum of two terms, the first of which being the corresponding term obtained as if phi were known, and the second, an additional term yielded by the fact that phi is unknown. The contribution of each set of parameters on the local powers of the tests can then be examined. Various implications of our main result are stated and discussed. Several examples are presented for illustrative purposes

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In this paper we obtain asymptotic expansions, up to order n(-1/2) and under a sequence of Pitman alternatives, for the nonnull distribution functions of the likelihood ratio, Wald, score and gradient test statistics in the class of symmetric linear regression models. This is a wide class of models which encompasses the t model and several other symmetric distributions with longer-than normal tails. The asymptotic distributions of all four statistics are obtained for testing a subset of regression parameters. Furthermore, in order to compare the finite-sample performance of these tests in this class of models, Monte Carlo simulations are presented. An empirical application to a real data set is considered for illustrative purposes. (C) 2011 Elsevier B.V. All rights reserved.

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The asymptotic expansion of the distribution of the gradient test statistic is derived for a composite hypothesis under a sequence of Pitman alternative hypotheses converging to the null hypothesis at rate n(-1/2), n being the sample size. Comparisons of the local powers of the gradient, likelihood ratio, Wald and score tests reveal no uniform superiority property. The power performance of all four criteria in one-parameter exponential family is examined.

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We derive asymptotic expansions for the nonnull distribution functions of the likelihood ratio, Wald, score and gradient test statistics in the class of dispersion models, under a sequence of Pitman alternatives. The asymptotic distributions of these statistics are obtained for testing a subset of regression parameters and for testing the precision parameter. Based on these nonnull asymptotic expansions, the power of all four tests, which are equivalent to first order, are compared. Furthermore, in order to compare the finite-sample performance of these tests in this class of models, Monte Carlo simulations are presented. An empirical application to a real data set is considered for illustrative purposes. (C) 2012 Elsevier B.V. All rights reserved.

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[EN] In this work, we present a new model for a dense disparity estimation and the 3-D geometry reconstruction using a color image stereo pair. First, we present a brief introduction to the 3-D Geometry of a camera system. Next, we propose a new model for the disparity estimation based on an energy functional. We look for the local minima of the energy using the associate Euler-Langrage partial differential equations. This model is a generalization to color image of the model developed in, with some changes in the strategy to avoid the irrelevant local minima. We present some numerical experiences of 3-D reconstruction, using this method some real stereo pairs.

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This thesis presents a creative and practical approach to dealing with the problem of selection bias. Selection bias may be the most important vexing problem in program evaluation or in any line of research that attempts to assert causality. Some of the greatest minds in economics and statistics have scrutinized the problem of selection bias, with the resulting approaches – Rubin’s Potential Outcome Approach(Rosenbaum and Rubin,1983; Rubin, 1991,2001,2004) or Heckman’s Selection model (Heckman, 1979) – being widely accepted and used as the best fixes. These solutions to the bias that arises in particular from self selection are imperfect, and many researchers, when feasible, reserve their strongest causal inference for data from experimental rather than observational studies. The innovative aspect of this thesis is to propose a data transformation that allows measuring and testing in an automatic and multivariate way the presence of selection bias. The approach involves the construction of a multi-dimensional conditional space of the X matrix in which the bias associated with the treatment assignment has been eliminated. Specifically, we propose the use of a partial dependence analysis of the X-space as a tool for investigating the dependence relationship between a set of observable pre-treatment categorical covariates X and a treatment indicator variable T, in order to obtain a measure of bias according to their dependence structure. The measure of selection bias is then expressed in terms of inertia due to the dependence between X and T that has been eliminated. Given the measure of selection bias, we propose a multivariate test of imbalance in order to check if the detected bias is significant, by using the asymptotical distribution of inertia due to T (Estadella et al. 2005) , and by preserving the multivariate nature of data. Further, we propose the use of a clustering procedure as a tool to find groups of comparable units on which estimate local causal effects, and the use of the multivariate test of imbalance as a stopping rule in choosing the best cluster solution set. The method is non parametric, it does not call for modeling the data, based on some underlying theory or assumption about the selection process, but instead it calls for using the existing variability within the data and letting the data to speak. The idea of proposing this multivariate approach to measure selection bias and test balance comes from the consideration that in applied research all aspects of multivariate balance, not represented in the univariate variable- by-variable summaries, are ignored. The first part contains an introduction to evaluation methods as part of public and private decision process and a review of the literature of evaluation methods. The attention is focused on Rubin Potential Outcome Approach, matching methods, and briefly on Heckman’s Selection Model. The second part focuses on some resulting limitations of conventional methods, with particular attention to the problem of how testing in the correct way balancing. The third part contains the original contribution proposed , a simulation study that allows to check the performance of the method for a given dependence setting and an application to a real data set. Finally, we discuss, conclude and explain our future perspectives.

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Questa tesi verte sullo studio di un modello a volatilità stocastica e locale, utilizzato per valutare opzioni esotiche nei mercati dei cambio. La difficoltà nell'implementare un modello di tal tipo risiede nella calibrazione della leverage surface e uno degli scopi principali di questo lavoro è quello di mostrarne la procedura.

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BACKGROUND: Mechanical pain sensitivity is assessed in every patient with pain, either by palpation or by quantitative pressure algometry. Despite widespread use, no studies have formally addressed the usefulness of this practice for the identification of the source of pain. We tested the hypothesis that assessing mechanical pain sensitivity distinguishes damaged from healthy cervical zygapophysial (facet) joints. METHODS: Thirty-three patients with chronic unilateral neck pain were studied. Pressure pain thresholds (PPTs) were assessed bilaterally at all cervical zygapophysial joints. The diagnosis of zygapophysial joint pain was made by selective nerve blocks. Primary analysis was the comparison of the PPT between symptomatic and contralateral asymptomatic joints. The secondary end points were as follows: differences in PPT between affected and asymptomatic joints of the same side of patients with zygapophysial joint pain; differences in PPT at the painful side between patients with and without zygapophysial joint pain; and sensitivity and specificity of PPT for 2 different cutoffs (difference in PPT between affected and contralateral side by 1 and 30 kPa, meaning that the test was considered positive if the difference in PPT between painful and contralateral side was negative by at least 1 and 30 kPa, respectively). The PPT of patients was also compared with the PPT of 12 pain-free subjects. RESULTS: Zygapophysial joint pain was present in 14 patients. In these cases, the difference in mean PPT between affected and contralateral side (primary analysis) was −6.2 kPa (95% confidence interval: −19.5 to 7.2, P = 0.34). In addition, the secondary analyses yielded no statistically significant differences. For the cutoff of 1 kPa, sensitivity and specificity of PPT were 67% and 16%, respectively, resulting in a positive likelihood ratio of 0.79 and a diagnostic confidence of 38%. When the cutoff of 30 kPa was considered, the sensitivity decreased to only 13%, whereas the specificity increased to 95%, resulting in a positive likelihood ratio of 2.53 and a diagnostic confidence of 67%. The PPT was significantly lower in patients than in pain-free subjects (P < 0.001). CONCLUSIONS: Assessing mechanical pain sensitivity is not diagnostic for cervical zygapophysial joint pain. The finding should stimulate further research into a diagnostic tool that is widely used in the clinical examination of patients with pain.

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BACKGROUND: Functional magnetic resonance imaging (fMRI) of fluorine-19 allows for the mapping of oxygen partial pressure within perfluorocarbons in the alveolar space (Pao(2)). Theoretically, fMRI-detected Pao(2) can be combined with the Fick principle approach, i.e., a mass balance of oxygen uptake by ventilation and delivery by perfusion, to quantify the ventilation-perfusion ratio (Va/Q) of a lung region: The mixed venous blood and the inspiratory oxygen fraction, which are equal for all lung regions, are measured. In addition, the local expiratory oxygen fraction and the end capillary oxygen content, both of which may differ between the lung regions, are calculated using the fMRI-detected Pao(2). We investigated this approach by numerical simulations and applied it to quantify local Va/Q in the perfluorocarbons during partial liquid ventilation. METHODS: Numerical simulations were performed to analyze the sensitivity of the Va/Q calculation and to compare this approach with another one proposed by Rizi et al. in 2004 (Magn Reson Med 2004;52:65-72). Experimentally, the method was used during partial liquid ventilation in 7 anesthetized pigs. The Pao(2) distribution in intraalveolar perflubron was measured by fluorine-19 MRI. Respiratory gas fractions together with arterial and mixed venous blood samples were taken to quantify oxygen partial pressure and content. Using the Fick principle, the local Va/Q was estimated. The impact of gravity (nondependent versus dependent) of perflubron dose (10 vs 20 mL/kg body weight) and of inspired oxygen fraction (Fio(2)) (0.4-1.0) on Va/Q was examined. RESULTS: In numerical simulations, the Fick principle proved to be appropriate over the Va/Q range from 0.02 to 2.5. Va/Q values were in acceptable agreement with the method published by Rizi et al. In the experimental setting, low mean Va/Q values were found in perflubron (confidence interval [CI] 0.08-0.29 with 20 mL/kg perflubron). At this dose, Va/Q in the nondependent lung was higher (CI 0.18-0.39) than in the dependent lung regions (CI 0.06-0.16; P = 0.006; Student t test). Differences depending on Fio(2) or perflubron dose were, however, small. CONCLUSION: The results show that derivation of Va/Q from local Po(2) measurements using fMRI in perflubron is feasible. The low detected Va/Q suggests that oxygen transport into the perflubron-filled alveolar space is significantly restrained.