89 resultados para Probability sample


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Objectives. The aims of this report were to describe the 5-year overall survival (OS) in a group of oral squamous cell carcinoma (OSCC) patients and to investigate the effects of age, gender, anatomic localization, tumor evolution time, smoking and alcohol intake, nodal status, tumoral recurrences, histologic classification, p53 and p63 immunoexpression, human papillomavirus DNA presence, and treatment on the prognostic outcome. Study design. Survival curves were generated using Kaplan-Meier method, and univariate and multivariate analyses were made using the log rank test and Cox regression, respectively. Results. The 5-year OS was 28.6%, and the univariate analysis showed significant results for p53 and p63 immunoexpression, age, and anatomic localization. The Cox regression demonstrated poor OS for tumors with p53 immunoexpression and for patients aged over 60 years. There were also significant differences in survival depending on the anatomic localizations. Conclusion. These results highlight the influence of p53 immunoexpression, age, and anatomic localization in OSCC evolution. (Oral Surg Oral Med Oral Pathol Oral Radiol Endod 2008; 106: 685-95)

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Background The objectives were to estimate the prevalence of hepatitis A among children and adolescents from the Northeast and Midwest regions and the Federal District of Brazil and to identify individual-, household- and area-levels factors associated with hepatitis A infection. Methods This population-based survey was conducted in 20042005 and covered individuals aged between 5 and 19 years. A stratified multistage cluster sampling technique with probability proportional to size was used to select 1937 individuals aged between 5 and 19 years living in the Federal capital and in the State capitals of 12 states in the study regions. The sample was stratified according to age (59 and 10- to 19-years-old) and capital within each region. Individual- and household-level data were collected by interview at the home of the individual. Variables related to the area were retrieved from census tract data. The outcome was total antibodies to hepatitis A virus detected using commercial EIA. The age distribution of the susceptible population was estimated using a simple catalytic model. The associations between HAV infection and independent variables were assessed using the odds ratio and corrected for the random design effect and sampling weight. Multilevel analysis was performed by GLLAMM using Stata 9.2. Results The prevalence of hepatitis A infection in the 59 and 1019 age-group was 41.5 and 57.4, respectively for the Northeast, 32.3 and 56.0, respectively for the Midwest and 33.8 and 65.1 for the Federal District. A trend for the prevalence of HAV infection to increase according to age was detected in all sites. By the age of 5, 31.5 of the children had already been infected with HAV in the Northeast region compared with 20.0 in the other sites. By the age of 19 years, seropositivity was 70 in all areas. The curves of susceptible populations differed from one area to another. Multilevel modeling showed that variables relating to different levels of education were associated with HAV infection in all sites. Conclusion The study sites were classified as areas with intermediate endemicity area for hepatitis A infection. Differences in age trends of infection were detected among settings. This multilevel model allowed for quantification of contextual predictors of hepatitis A infection in urban areas.

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The determination of the amount of sample units that will compose the sample express the optimization of the workforce, and reduce errors inherent in the report of recommendation and evaluation of soil fertility. This study aimed to determine in three systems use and soil management, the numbers of units samples design, needed to form the composed sample, for evaluation of soil fertility. It was concluded that the number of sample units needed to compose the composed sample to determination the attributes of organic matter, pH, P, K, Ca, Mg, Al and H+Al and base saturation of soil vary by use and soil management and error acceptable to the mean estimate. For the same depth of collected, increasing the number of sample units, reduced the percentage error in estimating the average, allowing the recommendation of 14, 14 and 11 sample in management with native vegetation, pasture cultivation and corn, respectively, for a error 20% on the mean estimate.

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Data from 58 strong-lensing events surveyed by the Sloan Lens ACS Survey are used to estimate the projected galaxy mass inside their Einstein radii by two independent methods: stellar dynamics and strong gravitational lensing. We perform a joint analysis of these two estimates inside models with up to three degrees of freedom with respect to the lens density profile, stellar velocity anisotropy, and line-of-sight (LOS) external convergence, which incorporates the effect of the large-scale structure on strong lensing. A Bayesian analysis is employed to estimate the model parameters, evaluate their significance, and compare models. We find that the data favor Jaffe`s light profile over Hernquist`s, but that any particular choice between these two does not change the qualitative conclusions with respect to the features of the system that we investigate. The density profile is compatible with an isothermal, being sightly steeper and having an uncertainty in the logarithmic slope of the order of 5% in models that take into account a prior ignorance on anisotropy and external convergence. We identify a considerable degeneracy between the density profile slope and the anisotropy parameter, which largely increases the uncertainties in the estimates of these parameters, but we encounter no evidence in favor of an anisotropic velocity distribution on average for the whole sample. An LOS external convergence following a prior probability distribution given by cosmology has a small effect on the estimation of the lens density profile, but can increase the dispersion of its value by nearly 40%.

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Technical actions performed by two groups of judokas who won medals at World Championships and Olympic Games during the period 1995-2001 were analyzed. In the Super Elite group (n = 17) were the best athletes in each weight category. The Elite group (n = 16) were medal winners who were not champions and did not win more than three medals. Super Elite judokas used a greater number of throwing techniques which resulted in scores, even when expressed relative to the total number of matches performed, and these techniques were applied in more directions than those of Elite judokas. Further, the number of different throwing techniques and the variability of directions in which techniques were applied were significantly correlated with number of wins and the number of points and ippon scored. Thus, a greater number of throwing techniques and use of directions for attack seem to be important in increasing unpredictability during judo matches.

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The use of bivariate distributions plays a fundamental role in survival and reliability studies. In this paper, we consider a location scale model for bivariate survival times based on the proposal of a copula to model the dependence of bivariate survival data. For the proposed model, we consider inferential procedures based on maximum likelihood. Gains in efficiency from bivariate models are also examined in the censored data setting. For different parameter settings, sample sizes and censoring percentages, various simulation studies are performed and compared to the performance of the bivariate regression model for matched paired survival data. Sensitivity analysis methods such as local and total influence are presented and derived under three perturbation schemes. The martingale marginal and the deviance marginal residual measures are used to check the adequacy of the model. Furthermore, we propose a new measure which we call modified deviance component residual. The methodology in the paper is illustrated on a lifetime data set for kidney patients.

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In interval-censored survival data, the event of interest is not observed exactly but is only known to occur within some time interval. Such data appear very frequently. In this paper, we are concerned only with parametric forms, and so a location-scale regression model based on the exponentiated Weibull distribution is proposed for modeling interval-censored data. We show that the proposed log-exponentiated Weibull regression model for interval-censored data represents a parametric family of models that include other regression models that are broadly used in lifetime data analysis. Assuming the use of interval-censored data, we employ a frequentist analysis, a jackknife estimator, a parametric bootstrap and a Bayesian analysis for the parameters of the proposed model. We derive the appropriate matrices for assessing local influences on the parameter estimates under different perturbation schemes and present some ways to assess global influences. Furthermore, for different parameter settings, sample sizes and censoring percentages, various simulations are performed; in addition, the empirical distribution of some modified residuals are displayed and compared with the standard normal distribution. These studies suggest that the residual analysis usually performed in normal linear regression models can be straightforwardly extended to a modified deviance residual in log-exponentiated Weibull regression models for interval-censored data. (C) 2009 Elsevier B.V. All rights reserved.

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Considering the Wald, score, and likelihood ratio asymptotic test statistics, we analyze a multivariate null intercept errors-in-variables regression model, where the explanatory and the response variables are subject to measurement errors, and a possible structure of dependency between the measurements taken within the same individual are incorporated, representing a longitudinal structure. This model was proposed by Aoki et al. (2003b) and analyzed under the bayesian approach. In this article, considering the classical approach, we analyze asymptotic test statistics and present a simulation study to compare the behavior of the three test statistics for different sample sizes, parameter values and nominal levels of the test. Also, closed form expressions for the score function and the Fisher information matrix are presented. We consider two real numerical illustrations, the odontological data set from Hadgu and Koch (1999), and a quality control data set.

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In this paper, we proposed a new two-parameter lifetime distribution with increasing failure rate, the complementary exponential geometric distribution, which is complementary to the exponential geometric model proposed by Adamidis and Loukas (1998). The new distribution arises on a latent complementary risks scenario, in which the lifetime associated with a particular risk is not observable; rather, we observe only the maximum lifetime value among all risks. The properties of the proposed distribution are discussed, including a formal proof of its probability density function and explicit algebraic formulas for its reliability and failure rate functions, moments, including the mean and variance, variation coefficient, and modal value. The parameter estimation is based on the usual maximum likelihood approach. We report the results of a misspecification simulation study performed in order to assess the extent of misspecification errors when testing the exponential geometric distribution against our complementary one in the presence of different sample size and censoring percentage. The methodology is illustrated on four real datasets; we also make a comparison between both modeling approaches. (C) 2011 Elsevier B.V. All rights reserved.

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In survival analysis applications, the failure rate function may frequently present a unimodal shape. In such case, the log-normal or log-logistic distributions are used. In this paper, we shall be concerned only with parametric forms, so a location-scale regression model based on the Burr XII distribution is proposed for modeling data with a unimodal failure rate function as an alternative to the log-logistic regression model. Assuming censored data, we consider a classic analysis, a Bayesian analysis and a jackknife estimator for the parameters of the proposed model. For different parameter settings, sample sizes and censoring percentages, various simulation studies are performed and compared to the performance of the log-logistic and log-Burr XII regression models. Besides, we use sensitivity analysis to detect influential or outlying observations, and residual analysis is used to check the assumptions in the model. Finally, we analyze a real data set under log-Buff XII regression models. (C) 2008 Published by Elsevier B.V.

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Ribbons of nominal composition (Pr(9.5)Fe(84.5)B(6))(0.96)Cr(0.01)(TiC)(0.03) were produced by arc-melting and melt-spinning the alloys on a Cu wheel. X-ray diffraction (XRD) reveals two main phases, one based upon alpha-Fe and the other upon Pr(2)Fe(14)B. The ribbons show exchange spring behavior with H (c) = 12.5 kOe and (BH)(max) = 13.6 MGOe when these two phases are well coupled. Transmission electron microscopy revealed the coupled behavior is observed when the microstructure consists predominantly of alpha-Fe grains (diameter similar to 100 nm.) surrounded by hard material containing Pr(2)Fe(14)B. The microstructure is discussed in terms of a calculation by Skomski and Coey. A first-order-reversal-curve (FORC) analysis was performed for both a well-coupled sample and a poorly coupled sample. The FORC diagrams show two strong peaks for both the poorly coupled sample and for the well-coupled material. In both cases, the localization of the FORC probability suggests magnetizing interactions between particles. Switching field distributions were calculated and are consistent with the sample microstructure.

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Ribbons of nominal composition (Pr(9.5)Fe(84.5)B(6))(0.96)Cr(0.01)(TiC)(0.03) were produced by arc-melting and melt-spinning the alloys on a Cu wheel. X-ray diffraction reveals two main phases, one based upon alpha-Fe and the other upon Pr(2)Fe(14)B. The ribbons show exchange spring behavior with H(c)=12.5 kOe and (BH)(max)= 13.6 MGOe when these two phases are well coupled. Transmission electron microscopy revealed that the coupled behavior is observed when the microstructure consists predominantly of alpha-Fe grains(diameter similar to 100 nm.) surrounded by hard material containing Pr(2)Fe(14)B. A first-order-reversal-curve (FORC) analysis was performed for both a well-coupled sample and a partially-coupled sample. The FORC diagrams show two strong peaks for both the partially-coupled sample and for the well coupled material. In both cases, the localization of the FORC probability suggests demagnetizing interactions between particles. Switching field distributions were calculated and are consistent with the sample microstructure. (C) 2009 Elsevier B.V. All rights reserved.

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Irradiation with heavy ions can produce several modifications in the chain structure of polymers. These modifications can be related to scissioning and cross-linking of chemical bonds. which depend on the ion fluence and the density of energy deposited in the material. Stacked thin film Makrofol-KG (R) samples were irradiated with 350 MeV Au(26+) ions and FTIR absorption spectroscopy was used to determine the bond changes in the samples. Data on the absorption bands as a function of the fluence indicated a higher probability for simple-bonds scissioning than for double-bonds scissioning and no dependence on the number of double bonds breaking with ion fluence. Since sample irradiation was done in a non-track-overlapping regime, a novel process for double bonds formation is suggested: the excitation of a site in the material by only one incident ion followed by a double bond formation during the de-excitation process. (C) 2009 Elsevier B.V. All rights reserved.

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Ancient potteries usually are made of the local clay material, which contains relatively high concentration of iron. The powdered samples are usually quite black, due to magnetite, and, although they can be used for thermoluminescene (TL) dating, it is easiest to obtain better TL reading when clearest natural or pre-treated sample is used. For electron paramagnetic resonance (EPR) measurements, the huge signal due to iron spin-spin interaction, promotes an intense interference overlapping any other signal in this range. Sample dating is obtained by dividing the radiation dose, determined by the concentration of paramagnetic species generated by irradiation, by the natural dose so as a consequence, EPR dating cannot be used, since iron signal do not depend on radiation dose. In some cases, the density separation method using hydrated solution of sodium polytungstate [Na(G)(H(2)W(12)O(40))center dot H(2)O] becomes useful. However, the sodium polytungstate is very expensive in Brazil: hence an alternative method for eliminating this interference is proposed. A chemical process to eliminate about 90% of magnetite was developed. A sample of powdered ancient pottery was treated in a mixture (3:1:1) of HCI, HNO(3) and H(2)O(2) for 4 h. After that, it was washed several times in distilled water to remove all acid matrixes. The original black sample becomes somewhat clearer. The resulting material was analyzed by plasma mass spectrometry (ICP-MS), with the result that the iron content is reduced by a factor of about 9. In EPR measurements a non-treated natural ceramic sample shows a broad spin-spin interaction signal, the chemically treated sample presents a narrow signal in g= 2.00 region, possibly due to a radical of (SiO(3))(3-), mixed with signal of remaining iron [M. lkeya, New Applications of Electron Spin Resonance, World Scientific, Singapore, 1993, p. 285]. This signal increases in intensity under -gamma-irradiation. However, still due to iron influence, the additive method yielded too old age-value. Since annealing at 300 degrees C, Toyoda and Ikeya IS. Toyoda, M. Ikeya, Geochem. J. 25 (1991) 427-445] states that E `(1)-signal with maximum intensity is obtained, while annealing at 400 degrees C E`(1)-signal is completely eliminated, the subtraction of the second one from 300 degrees C heat-treated sample isolate E`(1)-like signal. Since this is radiation dose-dependent, we show that now EPR dating becomes possible. (C) 2008 Elsevier B.V. All rights reserved.

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This work demonstrates that the detuning of the fs-laser spectrum from the two-photon absorption band of organic materials can be used to reach further control of the two-photon absorption by pulse spectral phase manipulation. We investigate the coherent control of the two-photon absorption in imidazole-thiophene core compounds presenting distinct two-photon absorption spectra. The coherent control, performed using pulse phase shaping and genetic algorithm, exhibited different growth rates for each sample. Such distinct trends were explained by calculating the two-photon absorption probability considering the intrapulse interference mechanism, taking into account the two-photon absorption spectrum of the samples. Our results indicate that tuning the relative position between the nonlinear absorption and the pulse spectrum can be used as a novel strategy to optimize the two-photon absorption in broadband molecular systems. (C) 2011 Elsevier B.V. All rights reserved.