884 resultados para Survival analysis (Biometry) Mathematical models


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Natural frequencies were analyzed (axial, torsional and flexural) and frequency response of a vertical rotor with a hard disk at the edge through the classical and complex modal analysis. The mathematical modeling was based on the theory of Euler-Bernoulli beam. The equation that rules the movement was obtained through the Lagrangian formulation. The model considered the effects of bending, torsion and axial deformation of the shaft, besides the gravitational and gyroscopic effects. The finite element method was used to discretize the structure into hollow cylindrical elements with 12 degrees of freedom. Mass, stiffness and gyroscopic matrices were explained consistently. This type of tool, based on the use of complex coordinates to describe the dynamic behavior of rotating shaft, allows the decomposition of the system in two submodes, backward and forward. Thus, it is possible to clearly visualize that the orbit and direction of the precessional motion around the line of the rotating shaft is not deformed. A finite element program was developed using Matlab ®, and numerical simulations were performed to validate this model.

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Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

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Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

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Pós-graduação em Agronomia (Ciência do Solo) - FCAV

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Studies with organic systems have shown the feasibility and ecological and social sustainability of these agroecosystems, unlike the systems agrochemicals (conventional) production. Some studies have concluded that for the model agrochemical exists less interaction between the flow of internal energy, basically the crop receives all inputs to production with no increase in "energy quality" within the system, while in the organic model of production has increased interaction between different resources in the system. The current economic and ecological crisis, exposed no sustainability of the production pattern of industrialized agriculture developed in a way, showing the dependence of developed countries on imports of agricultural commodities produced in the third world, among there coffee. Given these facts, developed a survey to identify problems in the Alta Paulista region, west of São Paulo State, in relation to coffee production systems. Actually, the fundamental problem, according to the research, farmers in this region, is to choose a viable production system correctly (environmental, social and economic); agrochemical or organic. The objectives of this study were to analyze the yield of production systems and agro-chemical and organic coffee in the period from 2003 to 2007, in 30 producing properties, located in this region, in order to point the production system to produce the highest yield. According to the methodology of CONAB, data collected were recorded on spreadsheets to be used as variables in statistical analysis models and mathematics. We performed a descriptive analysis of productivity data and were used for statistical analysis tests for parametric and nonparametric analysis of variance. The mathematical analyses of the curves were prepared with Origin for Windows 6.0 software, which uses numerical methods to fit the data supplied to a function of variable parameters. Unlike conventional systems of production, the organic system showed greater viability of the production model. Furthermore, with the quantitative modeling proposal, it is possible to perform the evaluation of these types of investments, providing more security to the farmer at the time of decision.

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Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

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In this paper we propose a hybrid hazard regression model with threshold stress which includes the proportional hazards and the accelerated failure time models as particular cases. To express the behavior of lifetimes the generalized-gamma distribution is assumed and an inverse power law model with a threshold stress is considered. For parameter estimation we develop a sampling-based posterior inference procedure based on Markov Chain Monte Carlo techniques. We assume proper but vague priors for the parameters of interest. A simulation study investigates the frequentist properties of the proposed estimators obtained under the assumption of vague priors. Further, some discussions on model selection criteria are given. The methodology is illustrated on simulated and real lifetime data set.

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Background: Many studies reported that brief interventions are effective in reducing excessive drinking. This study aimed to assess the efficacy of a protocol of brief intervention for college students (BASICS), delivered face-to-face, to reduce risky alcohol consumption and negative consequences. Methods: A systematic review with meta-analysis was performed by searching for randomized controlled trials (RCTs) in Medline, PsycInfo, Web of Science and Cochrane Library databases. A quality assessment of RCTs was made by using a validated scale. Combined mean effect sizes, using meta-analysis random-effects models, were calculated. Results: 18 studies were included in the review. The sample sizes ranged from 54 to 1275 (median = 212). All studies presented a good evaluation of methodological quality and four were found to have excellent quality. After approximately 12 months of follow-up, students receiving BASICS showed a significant reduction in alcohol consumption (difference between means = -1.50 drinks per week, 95% CI: -3.24 to -0.29) and alcohol-related problems (difference between means = -0.87, 95% CI: -1.58 to -0.20) compared to controls. Conclusions: Overall, BASICS lowered both alcohol consumption and negative consequences in college students. Gender and peer factors seem to play an important role as moderators of behavior change in college drinking. Characteristics of BASICS procedure have been evaluated as more favorable and acceptable by students in comparison with others interventions or control conditions. Considerations for future researches were discussed.

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Model diagnostics is an integral part of model determination and an important part of the model diagnostics is residual analysis. We adapt and implement residuals considered in the literature for the probit, logistic and skew-probit links under binary regression. New latent residuals for the skew-probit link are proposed here. We have detected the presence of outliers using the residuals proposed here for different models in a simulated dataset and a real medical dataset.

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Long-term survival models have historically been considered for analyzing time-to-event data with long-term survivors fraction. However, situations in which a fraction (1 - p) of systems is subject to failure from independent competing causes of failure, while the remaining proportion p is cured or has not presented the event of interest during the time period of the study, have not been fully considered in the literature. In order to accommodate such situations, we present in this paper a new long-term survival model. Maximum likelihood estimation procedure is discussed as well as interval estimation and hypothesis tests. A real dataset illustrates the methodology.

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For the first time, we introduce a generalized form of the exponentiated generalized gamma distribution [Cordeiro et al. The exponentiated generalized gamma distribution with application to lifetime data, J. Statist. Comput. Simul. 81 (2011), pp. 827-842.] that is the baseline for the log-exponentiated generalized gamma regression model. The new distribution can accommodate increasing, decreasing, bathtub- and unimodal-shaped hazard functions. A second advantage is that it includes classical distributions reported in the lifetime literature as special cases. We obtain explicit expressions for the moments of the baseline distribution of the new regression model. The proposed model can be applied to censored data since it includes as sub-models several widely known regression models. It therefore can be used more effectively in the analysis of survival data. We obtain maximum likelihood estimates for the model parameters by considering censored data. We show that our extended regression model is very useful by means of two applications to real data.

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Objective: To build a life table and determine the factors related to the time of treatment of undernourished children at a nutrition rehabilitation centre (CREN), Sao Paulo, Brazil. Design: Nutritional status was assessed from weight-for-age, height-for-age and BMI-for-age Z-scores, while neuropsychomotor development was classified according to the milestones of childhood development. Life tables, Kaplan-Meier survival curves and Cox multiple regression models were employed in data analysis. Setting: CREN (Centre of Nutritional Recovery and Education), Sao Paulo, Brazil. Subjects: Undernourished children (n 228) from the southern slums of Sao Paulo who had received treatment at CREN under a day-hospital regime between the years 1994 and 2009. Results: The Kaplan-Meier curves of survival analysis showed statistically significant differences in the periods of treatment at CREN between children presenting different degrees of neuropsychomotor development (log-rank = 6.621; P = 0.037). Estimates based on the multivariate Cox model revealed that children aged >= 24 months at the time of admission exhibited a lower probability of nutritional rehabilitation (hazard ratio (HR) = 0.49; P = 0.046) at the end of the period compared with infants aged up 12 months. Children presenting slow development were better rehabilitated in comparison with those exhibiting adequate evolution (HR = 4.48; P = 0.023). No significant effects of sex, degree of undernutrition or birth weight on the probability of nutritional rehabilitation were found. Conclusions: Age and neuropsychomotor developmental status at the time of admission to CREN are critical factors in determining the duration of treatment.

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In this paper we extend semiparametric mixed linear models with normal errors to elliptical errors in order to permit distributions with heavier and lighter tails than the normal ones. Penalized likelihood equations are applied to derive the maximum penalized likelihood estimates (MPLEs) which appear to be robust against outlying observations in the sense of the Mahalanobis distance. A reweighed iterative process based on the back-fitting method is proposed for the parameter estimation and the local influence curvatures are derived under some usual perturbation schemes to study the sensitivity of the MPLEs. Two motivating examples preliminarily analyzed under normal errors are reanalyzed considering some appropriate elliptical errors. The local influence approach is used to compare the sensitivity of the model estimates.

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In this work the differentiability of the principal eigenvalue lambda = lambda(1)(Gamma) to the localized Steklov problem -Delta u + qu = 0 in Omega, partial derivative u/partial derivative nu = lambda chi(Gamma)(x)u on partial derivative Omega, where Gamma subset of partial derivative Omega is a smooth subdomain of partial derivative Omega and chi(Gamma) is its characteristic function relative to partial derivative Omega, is shown. As a key point, the flux subdomain Gamma is regarded here as the variable with respect to which such differentiation is performed. An explicit formula for the derivative of lambda(1) (Gamma) with respect to Gamma is obtained. The lack of regularity up to the boundary of the first derivative of the principal eigenfunctions is a further intrinsic feature of the problem. Therefore, the whole analysis must be done in the weak sense of H(1)(Omega). The study is of interest in mathematical models in morphogenesis. (C) 2011 Elsevier Inc. All rights reserved.

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Abstract Background To test if the expression of Smad1-8 mRNAs were predictive of survival in patients with oral squamous cell carcinoma (SCC). Patients and Methods We analyzed, prospectively, the expression of Smad1-8, by means of Ribonuclease Protection Assay in 48 primary, operable, oral SCC. In addition, 21 larynx, 10 oropharynx and 4 hypopharynx SCC and 65 matched adjacent mucosa, available for study, were also included. For survival analysis, patients were categorized as positive or negative for each Smad, according to median mRNA expression. We also performed real-time quantitative PCR (QRTPCR) to asses the pattern of TGFβ1, TGFβ2, TGFβ3 in oral SCC. Results Our results showed that Smad2 and Smad6 mRNA expression were both associated with survival in Oral SCC patients. Cox Multivariate analysis revealed that Smad6 positivity and Smad2 negativity were both predictive of good prognosis for oral SCC patients, independent of lymph nodal status (P = 0.003 and P = 0.029, respectively). In addition, simultaneously Smad2- and Smad6+ oral SCC group of patients did not reach median overall survival (mOS) whereas the mOS of Smad2+/Smad6- subgroup was 11.6 months (P = 0.004, univariate analysis). Regarding to TGFβ isoforms, we found that Smad2 mRNA and TGFβ1 mRNA were inversely correlated (p = 0.05, R = -0.33), and that seven of the eight TGFβ1+ patients were Smad2-. In larynx SCC, Smad7- patients did not reach mOS whereas mOS of Smad7+ patients were only 7.0 months (P = 0.04). No other correlations were found among Smad expression, clinico-pathological characteristics and survival in oral, larynx, hypopharynx, oropharynx or the entire head and neck SCC population. Conclusion Smad6 together with Smad2 may be prognostic factors, independent of nodal status in oral SCC after curative resection. The underlying mechanism which involves aberrant TGFβ signaling should be better clarified in the future.