61 resultados para linear mixed-effects models
Resumo:
High-angle grain boundary migration is predicted during geometric dynamic recrystallization (GDRX) by two types of mathematical models. Both models consider the driving pressure due to curvature and a sinusoidal driving pressure owing to subgrain walls connected to the grain boundary. One model is based on the finite difference solution of a kinetic equation, and the other, on a numerical technique in which the boundary is subdivided into linear segments. The models show that an initially flat boundary becomes serrated, with the peak and valley migrating into both adjacent grains, as observed during GDRX. When the sinusoidal driving pressure amplitude is smaller than 2 pi, the boundary stops migrating, reaching an equilibrium shape. Otherwise, when the amplitude is larger than 2 pi, equilibrium is never reached and the boundary migrates indefinitely, which would cause the protrusions of two serrated parallel boundaries to impinge on each other, creating smaller equiaxed grains.
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Purpose: To study the oculometric parameters of hyperopia in children with esotropic amblyopia, comparing amblyopic eyes with fellow eyes. Methods: Thirty-seven patients (5-8 years old) with bilateral hyperopia and esotropic amblyopia underwent a comprehensive ophthalmic examination, including cycloplegic refraction, keratometry and A-scan ultrasonography. Anterior chamber depth, lens thickness, vitreous chamber depth and total axial length were recorded. The refractive power of the crystalline lens was calculated using Bennett`s equations. Paired Student`s t-tests were used to compare ocular biometric measurements between amblyopic eyes and their fellow eyes. The associations of biometric parameters with refractive errors were assessed using Pearson correlation coefficients and linear regression. Multivariable models including axial length, corneal power and lens power were also constructed. Results: Amblyopic eyes were found to have significantly more hyperopic refraction, less corneal power, greater lens power, shorter vitreous chamber depth and shorter axial length, despite similar anterior chamber depth and lens thickness. The strongest correlation with refractive error was observed for the axial length/corneal radius ratio (r(36) = -0.92, p < 0.001 for amblyopic and r(36) = 0.87, p < 0.001 for fellow eyes). Axial length accounted for 39.2% (R(2)) of the refractive error variance in amblyopic eyes and 35.5% in fellow eyes. Adding corneal power to the model increased R(2) to 85.7% and 79.6%, respectively. A statistically significant correlation was found between axial length and corneal power, indicating decreasing corneal power with increasing axial length, and they were similar for amblyopic eyes (r(36) = 0.53,p < 0.001) and fellow eyes (r(36) = -0.57, p < 0.001). A statistically significant correlation was also found between axial length and lens power, indicating decreasing lens power with increasing axial length (r(36) = -0.72, p < 0.001 for amblyopic eyes and r(36) = -0.69, p < 0.001 for fellow eyes). Conclusions: We observed that the correlation among the major oculometric parameters and their individual contribution to hyperopia in esotropic children were similar in amblyopic and non-amblyopic eyes. This finding suggests that the counterbalancing effect of greater corneal and lens power associated with shorter axial length is similar in both eyes of patients with esotropic amblyopia.
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Introduction: The association between serological markers with the need of biological therapy for early rheumatoid arthritis (ERA) is not known, with few available data addressing this question. Objectives: To prospectively evaluate a cohort of patients with ERA (less than 12 months of symptoms) in order to determine the possible association between serological markers (rheumatoid factor (RF), anti-cyclic citrullinated peptide antibodies (anti-CCP), and citrullinated anti-vimentin (anti-Sa) with parameters of therapeutic outcome (this later defined by the need of introducing biological therapy). Patients and methods: Forty patients with early RA were evaluated at the time of diagnosis and have been followed for 3 years, in use of standardized therapeutic treatment. Demographic and clinical data were recorded, as well as serology tests (ELISA) for RF (IgM, IgG and IgA), anti-CCP (CCP2, CCP3 and CCP3.1) and anti-Sa in the initial evaluation and at 3, 6, 12, 18, 24 and 36 months of follow-up. As outcomes of the RA development, the need or not for biological therapy during the follow-up period were considered. Comparisons were made through the Student t test, mixed-effects regression analysis and analysis of variance (significance level of 5%). Results: The mean age was 45 (+/- 12) years; a female predominance was observed (90%). At the time of diagnosis, RF was observed in 50% of cases (RF IgA - 42%, RF IgG - 30% and RF IgM - 50%), anti-CCP in 50% (no difference between CCP2, CCP3 and CCP3. 1) and anti-Sa in 10%. After 3 years, no change in the RF prevalence neither in the anti-CCP was observed, but the anti-Sa increased to 17.5% (p = 0.001). Biological therapy was necessary in 22.5% of patients. The mean RF IgA and anti-CCP 2 levels during the 3 years were higher among patients who needed biological therapy (p <0.05 for both). Conclusion: Higher titles of RF and anti-CCP over time were associated with the need for biological therapy.
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Background: The duodenum and proximal jejunum are excluded after Roux-en-Y gastric bypass but these intestinal sites are where iron and zinc are most absorbed. Therefore, they are among the nutrients whose digestive and absorptive process can be impaired after surgery. The aim of the present study was to investigate the iron and zinc plasma response to a tolerance test before and after bariatric surgery. The study was performed at Sao Paulo University School of Medicine of Ribeirao Preto, Brazil. Methods: In a longitudinal paired study, 9 morbidly obese women (body mass index >= 40 kg/m(2)) underwent an iron and zinc tolerance test before and 3 months after surgery. The iron and zinc levels were determined at 0, 1, 2, 3, and 4 hours after a physiologic unique oral dose. The mineral concentrations in die plasma and 24-hour urine sample were assayed using an atomic absorption spectrophotometer. The anthropometric measurements and 3-day food record were also evaluated. A linear mixed model was used to compare the plasma concentration versus interval after the oral dose, before and after surgery. Results: The pre- and postoperative test results revealed a significantly lower plasma zinc response (P <.01) and a delayed response to iron intake after surgery. The total plasma iron concentration area, during the 4 hours, was not different after surgery (P >.05). The 24-hour urinary iron and zinc excretion did not differ between the pre- and postoperative phases. Conclusion: The present data showed a compromised response to the zinc tolerance test after gastric bypass surgery, suggesting an impaired absorption of zinc. More attention must be devoted to zinc nutritional status after surgery. (Surg Obes Relat Dis 2011;7:309-314.) (C) 2011 American Society for Metabolic and Bariatric Surgery. All rights reserved.
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Broad-scale phylogenetic analyses of the angiosperms and of the Asteridae have failed to confidently resolve relationships among the major lineages of the campanulid Asteridae (i.e., the euasterid II of APG II, 2003). To address this problem we assembled presently available sequences for a core set of 50 taxa, representing the diversity of the four largest lineages (Apiales, Aquifoliales, Asterales, Dipsacales) as well as the smaller ""unplaced"" groups (e.g., Bruniaceae, Paracryphiaceae, Columelliaceae). We constructed four data matrices for phylogenetic analysis: a chloroplast coding matrix (atpB, matK, ndhF, rbcL), a chloroplast non-coding matrix (rps16 intron, trnT-F region, trnV-atpE IGS), a combined chloroplast dataset (all seven chloroplast regions), and a combined genome matrix (seven chloroplast regions plus 18S and 26S rDNA). Bayesian analyses of these datasets using mixed substitution models produced often well-resolved and supported trees. Consistent with more weakly supported results from previous studies, our analyses support the monophyly of the four major clades and the relationships among them. Most importantly, Asterales are inferred to be sister to a clade containing Apiales and Dipsacales. Paracryphiaceae is consistently placed sister to the Dipsacales. However, the exact relationships of Bruniaceae, Columelliaceae, and an Escallonia clade depended upon the dataset. Areas of poor resolution in combined analyses may be partly explained by conflict between the coding and non-coding data partitions. We discuss the implications of these results for our understanding of campanulid phylogeny and evolution, paying special attention to how our findings bear on character evolution and biogeography in Dipsacales.
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Mixed linear models are commonly used in repeated measures studies. They account for the dependence amongst observations obtained from the same experimental unit. Often, the number of observations is small, and it is thus important to use inference strategies that incorporate small sample corrections. In this paper, we develop modified versions of the likelihood ratio test for fixed effects inference in mixed linear models. In particular, we derive a Bartlett correction to such a test, and also to a test obtained from a modified profile likelihood function. Our results generalize those in [Zucker, D.M., Lieberman, O., Manor, O., 2000. Improved small sample inference in the mixed linear model: Bartlett correction and adjusted likelihood. Journal of the Royal Statistical Society B, 62,827-838] by allowing the parameter of interest to be vector-valued. Additionally, our Bartlett corrections allow for random effects nonlinear covariance matrix structure. We report simulation results which show that the proposed tests display superior finite sample behavior relative to the standard likelihood ratio test. An application is also presented and discussed. (C) 2008 Elsevier B.V. All rights reserved.
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Prediction of random effects is an important problem with expanding applications. In the simplest context, the problem corresponds to prediction of the latent value (the mean) of a realized cluster selected via two-stage sampling. Recently, Stanek and Singer [Predicting random effects from finite population clustered samples with response error. J. Amer. Statist. Assoc. 99, 119-130] developed best linear unbiased predictors (BLUP) under a finite population mixed model that outperform BLUPs from mixed models and superpopulation models. Their setup, however, does not allow for unequally sized clusters. To overcome this drawback, we consider an expanded finite population mixed model based on a larger set of random variables that span a higher dimensional space than those typically applied to such problems. We show that BLUPs for linear combinations of the realized cluster means derived under such a model have considerably smaller mean squared error (MSE) than those obtained from mixed models, superpopulation models, and finite population mixed models. We motivate our general approach by an example developed for two-stage cluster sampling and show that it faithfully captures the stochastic aspects of sampling in the problem. We also consider simulation studies to illustrate the increased accuracy of the BLUP obtained under the expanded finite population mixed model. (C) 2007 Elsevier B.V. All rights reserved.
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In this paper we extend partial linear models with normal errors to Student-t errors Penalized likelihood equations are applied to derive the maximum likelihood estimates which appear to be robust against outlying observations in the sense of the Mahalanobis distance In order to study the sensitivity of the penalized estimates under some usual perturbation schemes in the model or data the local influence curvatures are derived and some diagnostic graphics are proposed A motivating example preliminary analyzed under normal errors is reanalyzed under Student-t errors The local influence approach is used to compare the sensitivity of the model estimates (C) 2010 Elsevier B V All rights reserved
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Dental impression is an important step in the preparation of prostheses since it provides the reproduction of anatomic and surface details of teeth and adjacent structures. The objective of this study was to evaluate the linear dimensional alterations in gypsum dies obtained with different elastomeric materials, using a resin coping impression technique with individual shells. A master cast made of stainless steel with fixed prosthesis characteristics with two prepared abutment teeth was used to obtain the impressions. References points (A, B, C, D, E and F) were recorded on the occlusal and buccal surfaces of abutments to register the distances. The impressions were obtained using the following materials: polyether, mercaptan-polysulfide, addition silicone, and condensation silicone. The transfer impressions were made with custom trays and an irreversible hydrocolloid material and were poured with type IV gypsum. The distances between identified points in gypsum dies were measured using an optical microscope and the results were statistically analyzed by ANOVA (p < 0.05) and Tukey's test. The mean of the distances were registered as follows: addition silicone (AB = 13.6 µm, CD=15.0 µm, EF = 14.6 µm, GH=15.2 µm), mercaptan-polysulfide (AB = 36.0 µm, CD = 36.0 µm, EF = 39.6 µm, GH = 40.6 µm), polyether (AB = 35.2 µm, CD = 35.6 µm, EF = 39.4 µm, GH = 41.4 µm) and condensation silicone (AB = 69.2 µm, CD = 71.0 µm, EF = 80.6 µm, GH = 81.2 µm). All of the measurements found in gypsum dies were compared to those of a master cast. The results demonstrated that the addition silicone provides the best stability of the compounds tested, followed by polyether, polysulfide and condensation silicone. No statistical differences were obtained between polyether and mercaptan-polysulfide materials.
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We present measurements of J/psi yields in d + Au collisions at root S(NN) = 200 GeV recorded by the PHENIX experiment and compare them with yields in p + p collisions at the same energy per nucleon-nucleon collision. The measurements cover a large kinematic range in J/psi rapidity (-2.2 < y < 2.4) with high statistical precision and are compared with two theoretical models: one with nuclear shadowing combined with final state breakup and one with coherent gluon saturation effects. In order to remove model dependent systematic uncertainties we also compare the data to a simple geometric model. The forward rapidity data are inconsistent with nuclear modifications that are linear or exponential in the density weighted longitudinal thickness, such as those from the final state breakup of the bound state.
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The aims of the present study were to compare the effects of two periodization models on metabolic syndrome risk factors in obese adolescents and verify whether the angiotensin-converting enzyme (ACE) genotype is important in establishing these effects. A total of 32 postpuberty obese adolescents were submitted to aerobic training (AT) and resistance training (RT) for 14 weeks. The subjects were divided into linear periodization (LP, n = 16) or daily undulating periodization (DUP, n = 16). Body composition, visceral and subcutaneous fat, glycemia, insulinemia, homeostasis model assessment of insulin resistance (HOMA-IR), lipid profiles, blood pressure, maximal oxygen consumption (VO(2max)), resting metabolic rate (RMR), muscular endurance were analyzed at baseline and after intervention. Both groups demonstrated a significant reduction in body mass, BMI, body fat, visceral and subcutaneous fat, total and low-density lipoprotein cholesterol, blood pressure and an increase in fat-free mass, VO(2max), and muscular endurance. However, only DUP promoted a reduction in insulin concentrations and HOMA-IR. It is important to emphasize that there was no statics difference between LP and DUP groups; however, it appears that there may be bigger changes in the DUP than LP group in some of the metabolic syndrome risk factors in obese adolescents with regard to the effect size (ES). Both periodization models presented a large effect on muscular endurance. Despite the limitation of sample size, our results suggested that the ACE genotype may influence the functional and metabolic characteristics of obese adolescents and may be considered in the future strategies for massive obesity control.
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This work examines the effect of weld strength mismatch on fracture toughness measurements defined by J and CTOD fracture parameters using single edge notch bend (SE(B)) specimens. A central objective of the present study is to enlarge on previous developments of J and CTOD estimation procedures for welded bend specimens based upon plastic eta factors (eta) and plastic rotational factors (r (p) ). Very detailed non-linear finite element analyses for plane-strain models of standard SE(B) fracture specimens with a notch located at the center of square groove welds and in the heat affected zone provide the evolution of load with increased crack mouth opening displacement required for the estimation procedure. One key result emerging from the analyses is that levels of weld strength mismatch within the range +/- 20% mismatch do not affect significantly J and CTOD estimation expressions applicable to homogeneous materials, particularly for deeply cracked fracture specimens with relatively large weld grooves. The present study provides additional understanding on the effect of weld strength mismatch on J and CTOD toughness measurements while, at the same time, adding a fairly extensive body of results to determine parameters J and CTOD for different materials using bend specimens with varying geometries and mismatch levels.
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Survival models involving frailties are commonly applied in studies where correlated event time data arise due to natural or artificial clustering. In this paper we present an application of such models in the animal breeding field. Specifically, a mixed survival model with a multivariate correlated frailty term is proposed for the analysis of data from over 3611 Brazilian Nellore cattle. The primary aim is to evaluate parental genetic effects on the trait length in days that their progeny need to gain a commercially specified standard weight gain. This trait is not measured directly but can be estimated from growth data. Results point to the importance of genetic effects and suggest that these models constitute a valuable data analysis tool for beef cattle breeding.
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Mixed models have become important in analyzing the results of experiments, particularly those that require more complicated models (e.g., those that involve longitudinal data). This article describes a method for deriving the terms in a mixed model. Our approach extends an earlier method by Brien and Bailey to explicitly identify terms for which autocorrelation and smooth trend arising from longitudinal observations need to be incorporated in the model. At the same time we retain the principle that the model used should include, at least, all the terms that are justified by the randomization. This is done by dividing the factors into sets, called tiers, based on the randomization and determining the crossing and nesting relationships between factors. The method is applied to formulate mixed models for a wide range of examples. We also describe the mixed model analysis of data from a three-phase experiment to investigate the effect of time of refinement on Eucalyptus pulp from four different sources. Cubic smoothing splines are used to describe differences in the trend over time and unstructured covariance matrices between times are found to be necessary.
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This paper proposes a regression model considering the modified Weibull distribution. This distribution can be used to model bathtub-shaped failure rate functions. Assuming censored data, we consider maximum likelihood and Jackknife estimators for the parameters of the model. We derive the appropriate matrices for assessing local influence on the parameter estimates under different perturbation schemes and we also present some ways to perform global influence. Besides, for different parameter settings, sample sizes and censoring percentages, various simulations are performed and the empirical distribution of the modified deviance residual is 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 for a martingale-type residual in log-modified Weibull regression models with censored data. Finally, we analyze a real data set under log-modified Weibull regression models. A diagnostic analysis and a model checking based on the modified deviance residual are performed to select appropriate models. (c) 2008 Elsevier B.V. All rights reserved.