23 resultados para Linear mixed effect models


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The scope of this study was to estimate calibrated values for dietary data obtained by the Food Frequency Questionnaire for Adolescents (FFQA) and illustrate the effect of this approach on food consumption data. The adolescents were assessed on two occasions, with an average interval of twelve months. In 2004, 393 adolescents participated, and 289 were then reassessed in 2005. Dietary data obtained by the FFQA were calibrated using the regression coefficients estimated from the average of two 24-hour recalls (24HR) of the subsample. The calibrated values were similar to the the 24HR reference measurement in the subsample. In 2004 and 2005 a significant difference was observed between the average consumption levels of the FFQA before and after calibration for all nutrients. With the use of calibrated data the proportion of schoolchildren who had fiber intake below the recommended level increased. Therefore, it is seen that calibrated data can be used to obtain adjusted associations due to reclassification of subjects within the predetermined categories.

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A rigorous asymptotic theory for Wald residuals in generalized linear models is not yet available. The authors provide matrix formulae of order O(n(-1)), where n is the sample size, for the first two moments of these residuals. The formulae can be applied to many regression models widely used in practice. The authors suggest adjusted Wald residuals to these models with approximately zero mean and unit variance. The expressions were used to analyze a real dataset. Some simulation results indicate that the adjusted Wald residuals are better approximated by the standard normal distribution than the Wald residuals.

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Spatial linear models have been applied in numerous fields such as agriculture, geoscience and environmental sciences, among many others. Spatial dependence structure modelling, using a geostatistical approach, is an indispensable tool to estimate the parameters that define this structure. However, this estimation may be greatly affected by the presence of atypical observations in the sampled data. The purpose of this paper is to use diagnostic techniques to assess the sensitivity of the maximum-likelihood estimators, covariance functions and linear predictor to small perturbations in the data and/or the spatial linear model assumptions. The methodology is illustrated with two real data sets. The results allowed us to conclude that the presence of atypical values in the sample data have a strong influence on thematic maps, changing the spatial dependence structure.

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In this study, catalysts containing 5 wt.% Ni deposited on a support composed of a CeO2-ZrO2 solid solution deposited on alumina were tested in the steam reforming of methane. The supports, with various ratios of Ce to Zr, were prepared by co-precipitation of the oxide precursors, followed by calcination in synthetic air. The catalysts were then prepared by Ni impregnation of the supports. The prepared solids were characterized by temperature-programmed reduction with H-2 (TPR-H-2), in situ X-ray diffraction (XRD) and X-ray absorption near-edge structure (XANES) spectroscopy. The XRD analysis confirmed the formation of a solid solution between ZrO2 and CeO2. In the catalytic tests, it was found that catalysts with higher Ce content did not exhibit deactivation during 6 h of reaction. The catalyst with highest Ce content, Ni(0.8Ce0.2Zr)AI, provided the best result, with the highest rate of conversion of methane and the lowest carbon deposition, which may be partly due to the smaller Ni-0 crystallites in this sample and also the segregated CeO2 particles may have favored H2O adsorption which could lead to higher C gasification. (C) 2012 Elsevier B.V. All rights reserved.

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Insulin-like growth factor type 1 (IGF1) is a mediator of growth hormone (GH) action, and therefore, IGF1 is a candidate gene for recombinant human GH (rhGH) pharmacogenetics. Lower serum IGF1 levels were found in adults homozygous for 19 cytosine-adenosine (CA) repeats in the IGF1 promoter. The aim of this study was to evaluate the influence of (CA)n IGF1 polymorphism, alone or in combination with GH receptor (GHR)-exon 3 and -202 A/C insulin-like growth factor binding protein-3 (IGFBP3) polymorphisms, on the growth response to rhGH therapy in GH-deficient (GHD) patients. Eighty-four severe GHD patients were genotyped for (CA) n IGF1, -202 A/C IGFBP3 and GHR-exon 3 polymorphisms. Multiple linear regressions were performed to estimate the effect of each genotype, after adjustment for other influential factors. We assessed the influence of genotypes on the first year growth velocity (1st y GV) (n = 84) and adult height standard deviation score (SDS) adjusted for target-height SDS (AH-TH SDS) after rhGH therapy (n = 37). Homozygosity for the IGF1 19CA repeat allele was negatively correlated with 1st y GV (P = 0.03) and AH-TH SDS (P = 0.002) in multiple linear regression analysis. In conjunction with clinical factors, IGF1 and IGFBP3 genotypes explain 29% of the 1st y GV variability, whereas IGF1 and GHR polymorphisms explain 59% of final height-target-height SDS variability. We conclude that homozygosity for IGF1 (CA) 19 allele is associated with less favorable short-and long-term growth outcomes after rhGH treatment in patients with severe GHD. Furthermore, this polymorphism exhibits a non-additive interaction with -202 A/C IGFBP3 genotype on the 1st y GV and with GHR-exon 3 genotype on adult height. The Pharmacogenomics Journal (2012) 12, 439-445; doi:10.1038/tpj.2011.13; published online 5 April 2011

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A total of 46,089 individual monthly test-day (TD) milk yields (10 test-days), from 7,331 complete first lactations of Holstein cattle were analyzed. A standard multivariate analysis (MV), reduced rank analyses fitting the first 2, 3, and 4 genetic principal components (PC2, PC3, PC4), and analyses that fitted a factor analytic structure considering 2, 3, and 4 factors (FAS2, FAS3, FAS4), were carried out. The models included the random animal genetic effect and fixed effects of the contemporary groups (herd-year-month of test-day), age of cow (linear and quadratic effects), and days in milk (linear effect). The residual covariance matrix was assumed to have full rank. Moreover, 2 random regression models were applied. Variance components were estimated by restricted maximum likelihood method. The heritability estimates ranged from 0.11 to 0.24. The genetic correlation estimates between TD obtained with the PC2 model were higher than those obtained with the MV model, especially on adjacent test-days at the end of lactation close to unity. The results indicate that for the data considered in this study, only 2 principal components are required to summarize the bulk of genetic variation among the 10 traits.

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We consider modifications of the nonlinear Schrodinger model (NLS) to look at the recently introduced concept of quasi-integrability. We show that such models possess an in finite number of quasi-conserved charges which present intriguing properties in relation to very specific space-time parity transformations. For the case of two-soliton solutions where the fields are eigenstates of this parity, those charges are asymptotically conserved in the scattering process of the solitons. Even though the charges vary in time their values in the far past and the far future are the same. Such results are obtained through analytical and numerical methods, and employ adaptations of algebraic techniques used in integrable field theories. Our findings may have important consequences on the applications of these models in several areas of non-linear science. We make a detailed numerical study of the modified NLS potential of the form V similar to (vertical bar psi vertical bar(2))(2+epsilon), with epsilon being a perturbation parameter. We perform numerical simulations of the scattering of solitons for this model and find a good agreement with the results predicted by the analytical considerations. Our paper shows that the quasi-integrability concepts recently proposed in the context of modifications of the sine-Gordon model remain valid for perturbations of the NLS model.

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Setup operations are significant in some production environments. It is mandatory that their production plans consider some features, as setup state conservation across periods through setup carryover and crossover. The modelling of setup crossover allows more flexible decisions and is essential for problems with long setup times. This paper proposes two models for the capacitated lot-sizing problem with backlogging and setup carryover and crossover. The first is in line with other models from the literature, whereas the second considers a disaggregated setup variable, which tracks the starting and completion times of the setup operation. This innovative approach permits a more compact formulation. Computational results show that the proposed models have outperformed other state-of-the-art formulation.