946 resultados para Interactive fixed effects
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Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)
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Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)
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Pós-graduação em Genética e Melhoramento Animal - FCAV
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Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)
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Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)
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Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)
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We develop spatial statistical models for stream networks that can estimate relationships between a response variable and other covariates, make predictions at unsampled locations, and predict an average or total for a stream or a stream segment. There have been very few attempts to develop valid spatial covariance models that incorporate flow, stream distance, or both. The application of typical spatial autocovariance functions based on Euclidean distance, such as the spherical covariance model, are not valid when using stream distance. In this paper we develop a large class of valid models that incorporate flow and stream distance by using spatial moving averages. These methods integrate a moving average function, or kernel, against a white noise process. By running the moving average function upstream from a location, we develop models that use flow, and by construction they are valid models based on stream distance. We show that with proper weighting, many of the usual spatial models based on Euclidean distance have a counterpart for stream networks. Using sulfate concentrations from an example data set, the Maryland Biological Stream Survey (MBSS), we show that models using flow may be more appropriate than models that only use stream distance. For the MBSS data set, we use restricted maximum likelihood to fit a valid covariance matrix that uses flow and stream distance, and then we use this covariance matrix to estimate fixed effects and make kriging and block kriging predictions.
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Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)
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The objectives of the present study were to determine if variance components of calving intervals varied with age at calving and if considering calving intervals as a longitudinal trait would be a useful approach for fertility analysis of Zebu dairy herds. With these purposes, calving records from females born from 1940 to 2006 in a Guzerat dairy subpopulation in Brazil were analyzed. The fixed effects of contemporary groups, formed by year and farm at birth or at calving, and the regressions of age at calving, equivalent inbreeding coefficient and day of the year on the studied traits were considered in the statistical models. In one approach, calving intervals (Cl) were analyzed as a single trait, by fitting a statistical model on which both animal and permanent environment effects were adjusted for the effect of age at calving by random regression. In a second approach, a four-trait analysis was conducted, including age at first calving (AFC) and three different female categories for the calving intervals: first calving females; young females (less than 80 months old, but not first calving); or mature females (80 months old or more). Finally, a two-trait analysis was performed, also including AFC and Cl, but calving intervals were regarded as a single trait in a repeatability model. Additionally, the ranking of sires was compared among approaches. Calving intervals decreased with age until females were about 80 months old, remaining nearly constant after that age. A quasi-linear increase of 11.5 days on the calving intervals was observed for each 10% increase in the female's equivalent inbreeding coefficient. The heritability of AFC was 0.37. For Cl. the genetic-phenotypic variance ratios ranged from 0.064 to 0.141, depending on the approach and on ages at calving. Differences among genetic variance components for calving intervals were observed along the animal's lifetime. Those differences confirmed the longitudinal aspect of that trait, indicating the importance of such consideration when accessing fertility of Zebu dairy females, especially in situations where the available information relies on their calving intervals. Spearman rank correlations among approaches ranged from 0.90 to 0.95, and changes observed in the ranking of sires suggested that the genetic progress of the population could be affected by the approach chosen for the analysis of calving intervals. (C) 2012 Elsevier ay. All rights reserved.
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The objective of this research was to use non-linear models to describe the growth pattern in Santa Ines sheep and to study the influence of environmental effects on curve parameters with the best-fit model. The models included the Brody, Richards, Von Bertalanffy, Gompertz, and Logistic models. We used 773 field reports on 162 animals ranging in age from 120 to 774 days, including 46 males and 116 females. The statistics used to evaluate the quality of fit included RMS (residual mean square), C% (percentage of convergence), R-2 (adjusted determination coefficient) and MAD (mean absolute deviation). Of the fixed effects studied, the only significant relationship was the effect of sex on parameter A. The Richards model was problematic during the process of convergence. Considering all studied criteria, the Logistic model presented the best fit in describing the growth pattern in Santa Ines sheep. (C) 2011 Elsevier B.V. All rights reserved.
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Background: Infant mortality is an important measure of human development, related to the level of welfare of a society. In order to inform public policy, various studies have tried to identify the factors that influence, at an aggregated level, infant mortality. The objective of this paper is to analyze the regional pattern of infant mortality in Brazil, evaluating the effect of infrastructure, socio-economic, and demographic variables to understand its distribution across the country. Methods: Regressions including socio-economic and living conditions variables are conducted in a structure of panel data. More specifically, a spatial panel data model with fixed effects and a spatial error autocorrelation structure is used to help to solve spatial dependence problems. The use of a spatial modeling approach takes into account the potential presence of spillovers between neighboring spatial units. The spatial units considered are Minimum Comparable Areas, defined to provide a consistent definition across Census years. Data are drawn from the 1980, 1991 and 2000 Census of Brazil, and from data collected by the Ministry of Health (DATASUS). In order to identify the influence of health care infrastructure, variables related to the number of public and private hospitals are included. Results: The results indicate that the panel model with spatial effects provides the best fit to the data. The analysis confirms that the provision of health care infrastructure and social policy measures (e. g. improving education attainment) are linked to reduced rates of infant mortality. An original finding concerns the role of spatial effects in the analysis of IMR. Spillover effects associated with health infrastructure and water and sanitation facilities imply that there are regional benefits beyond the unit of analysis. Conclusions: A spatial modeling approach is important to produce reliable estimates in the analysis of panel IMR data. Substantively, this paper contributes to our understanding of the physical and social factors that influence IMR in the case of a developing country.
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This paper uses administrative data to follow Brazilian workers over time and examine what happens to the inter-regional wage differentials after controlling for unmeasured workers' characteristics that are fixed over time. Since the data allow us to track the same workers over the years, we are in the unusual position of obtaining the individual wages before and after the migration process. As a significant share of workers changed States in the sample period, it is possible to examine to what extent the wage differentials reflect the concentration of high-skilled individuals in some States. The results show that the overall wage variability across States drops to almost one third of its original value and the ranking of the State effects is significantly altered after we take into account the workers' fixed effects. A great deal of the inter-regional differentials, therefore, reflects differences in the average ability of workers across States.
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The aim of the present study was to estimate genetic parameters for flight speed and its association with growth traits in Nellore beef cattle. The flight speed (FS) of 7,402 yearling animals was measured, using a device composed of a pair of photoelectric cells. Time interval data (s) were converted to speed (m/s) and faster animals were regarded as more reactive. The growth traits analyzed were weaning weight (WW), ADG from weaning to yearling age, and yearling scrotal circumference (SC). The (co)variance components were estimated using REML in a multitrait analysis applying an animal model. The model included random direct additive genetic and residual effects, fixed effects of contemporary groups, age of dam (classes), and age of animal as covariable. For WW, the model also included maternal genetic and permanent environmental random effects. The direct heritability estimate for FS was 0.26 +/- 0.05 and direct heritability estimates for WW, SC, and ADG were 0.30 +/- 0.01, 0.48 +/- 0.02, and 0.19 +/- 0.01, respectively. Estimates of the genetic correlation between FS and the growth traits were -0.12 +/- 0.07 (WW), -0.13 +/- 0.08 (ADG), and -0.11 +/- 0.07 (SC). Although the values were low, these correlations showed that animals with better temperaments (slower FS) tended to present better performance. It is possible to infer that long-term selection for weight and scrotal circumference can promote a positive genetic response in the temperament of animals. Nevertheless, to obtain faster genetic progress in temperament, it would be necessary to perform direct selection for such trait. Flight speed is an easily measured indicator of temperament and can be included as a selection criterion in breeding programs for Nellore cattle.
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Context Lung-protective mechanical ventilation with the use of lower tidal volumes has been found to improve outcomes of patients with acute respiratory distress syndrome (ARDS). It has been suggested that use of lower tidal volumes also benefits patients who do not have ARDS. Objective To determine whether use of lower tidal volumes is associated with improved outcomes of patients receiving ventilation who do not have ARDS. Data Sources MEDLINE, CINAHL, Web of Science, and Cochrane Central Register of Controlled Trials up to August 2012. Study Selection Eligible studies evaluated use of lower vs higher tidal volumes in patients without ARDS at onset of mechanical ventilation and reported lung injury development, overall mortality, pulmonary infection, atelectasis, and biochemical alterations. Data Extraction Three reviewers extracted data on study characteristics, methods, and outcomes. Disagreement was resolved by consensus. Data Synthesis Twenty articles (2822 participants) were included. Meta-analysis using a fixed-effects model showed a decrease in lung injury development (risk ratio [RR], 0.33; 95% CI, 0.23 to 0.47; I-2, 0%; number needed to treat [NNT], 11), and mortality (RR, 0.64; 95% CI, 0.46 to 0.89; I-2, 0%; NNT, 23) in patients receiving ventilation with lower tidal volumes. The results of lung injury development were similar when stratified by the type of study (randomized vs nonrandomized) and were significant only in randomized trials for pulmonary infection and only in nonrandomized trials for mortality. Meta-analysis using a random-effects model showed, in protective ventilation groups, a lower incidence of pulmonary infection (RR, 0.45; 95% CI, 0.22 to 0.92; I-2, 32%; NNT, 26), lower mean (SD) hospital length of stay (6.91 [2.36] vs 8.87 [2.93] days, respectively; standardized mean difference [SMD], 0.51; 95% CI, 0.20 to 0.82; I-2, 75%), higher mean (SD) PaCO2 levels (41.05 [3.79] vs 37.90 [4.19] mm Hg, respectively; SMD, -0.51; 95% CI, -0.70 to -0.32; I-2, 54%), and lower mean (SD) pH values (7.37 [0.03] vs 7.40 [0.04], respectively; SMD, 1.16; 95% CI, 0.31 to 2.02; I-2, 96%) but similar mean (SD) ratios of PaO2 to fraction of inspired oxygen (304.40 [65.7] vs 312.97 [68.13], respectively; SMD, 0.11; 95% CI, -0.06 to 0.27; I-2, 60%). Tidal volume gradients between the 2 groups did not influence significantly the final results. Conclusions Among patients without ARDS, protective ventilation with lower tidal volumes was associated with better clinical outcomes. Some of the limitations of the meta-analysis were the mixed setting of mechanical ventilation (intensive care unit or operating room) and the duration of mechanical ventilation. JAMA. 2012;308(16):1651-1659 www.jama.com
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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.