927 resultados para LINEAR-REGRESSION MODELS
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Descreve-se o uso da análise fatorial na avaliação dos hábitos alimentares de nipo-brasileiros. Utilizaram-se dados dietéticos de 1.283 participantes de estudo transversal. A partir de critérios estatísticos e do significado conceitual dos padrões identificados, geraram-se escores que definiram os perfis dietéticos (japonês ou ocidental). Empregou-se o teste t de Student pareado, os modelos de regressão linear e de Poisson para examinar as relações desses escores com, respectivamente, a geração, índice de massa corporal (IMC), perímetro abdominal e a presença de síndrome metabólica. Aqueles de primeira geração, em relação aos de segunda, apresentaram escores maiores para o perfil japonês e menores para o ocidental. O perfil ocidental relacionou-se com o IMC (p = 0,001), perímetro abdominal (p = 0,023) e a síndrome metabólica (p < 0,05). Conclui-se que os escores discriminaram sujeitos que mantêm ou não estilo de vida tradicional japonês e que a incorporação de hábitos ocidentais associou-se a maiores valores de IMC, perímetro abdominal e a presença de síndrome metabólica
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Chronic diseases that are typical of adulthood may originate in intra-uterine life through inadequate fetal development. The present epidemiological cohort study of 506 healthy children aged 5\20138 years evaluated the relationship between birth weight and insulin resistance in an age group that has been assessed in few similar studies. Insulin concentration was determined by chemiluminescence and insulin resistance by the homeostasis model assessment (HOMA). Blood glucose, total cholesterol and fractions (LDL cholesterol and HDL cholesterol) and TAG concentrations were determined by automated enzymatic methods. Linear regression analysis investigated the relationship between birth weight (assessed as a continuous variable and in three categories: small for gestational age, SGA; adequate for gestational age and large for gestational age) and the HOMA index, using backward stepwise selection and biological models to explain the causal pathway of the relationship. There were negativeassociations between birth weight (P < 0·001), SGA (P = 0·027) and the HOMA index, and a positive association between waist circumference (P < 0·001) and the HOMA index. Considering the significant associations between birth weight and waist circumference (P < 0·001) and waist circumference and insulin resistance (P < 0·001), we can probably suspect that lower birth weight is a common cause of higher waist circumference and insulin resistance. In summary, the results of the present study showed increased insulin resistance in apparently healthy, young children, who had lower weight at birth and higher measurements of waist circumference. There is a need to develop public health policies that adopt preventive measures to promote adequate maternal-fetal and child development and enable early diagnosis of metabolic abnormalities
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Diagnostic methods have been an important tool in regression analysis to detect anomalies, such as departures from error assumptions and the presence of outliers and influential observations with the fitted models. Assuming censored data, we considered a classical analysis and Bayesian analysis assuming no informative priors for the parameters of the model with a cure fraction. A Bayesian approach was considered by using Markov Chain Monte Carlo Methods with Metropolis-Hasting algorithms steps to obtain the posterior summaries of interest. Some influence methods, such as the local influence, total local influence of an individual, local influence on predictions and generalized leverage were derived, analyzed and discussed in survival data with a cure fraction and covariates. The relevance of the approach was illustrated with a real data set, where it is shown that, by removing the most influential observations, the decision about which model best fits the data is changed.
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Background: Patients with chronic obstructive pulmonary disease (COPD) can have recurrent disease exacerbations triggered by several factors, including air pollution. Visits to the emergency respiratory department can be a direct result of short-term exposure to air pollution. The aim of this study was to investigate the relationship between the daily number of COPD emergency department visits and the daily environmental air concentrations of PM(10), SO(2), NO(2), CO and O(3) in the City of Sao Paulo, Brazil. Methods: The sample data were collected between 2001 and 2003 and are categorised by gender and age. Generalised linear Poisson regression models were adopted to control for both short-and long-term seasonal changes as well as for temperature and relative humidity. The non-linear dependencies were controlled using a natural cubic spline function. Third-degree polynomial distributed lag models were adopted to estimate both lag structures and the cumulative effects of air pollutants. Results: PM(10) and SO(2) readings showed both acute and lagged effects on COPD emergency department visits. Interquartile range increases in their concentration (28.3 mg/m(3) and 7.8 mg/m(3), respectively) were associated with a cumulative 6-day increase of 19% and 16% in COPD admissions, respectively. An effect on women was observed at lag 0, and among the elderly the lag period was noted to be longer. Increases in CO concentration showed impacts in the female and elderly groups. NO(2) and O(3) presented mild effects on the elderly and in women, respectively. Conclusion: These results indicate that air pollution affects health in a gender-and age-specific manner and should be considered a relevant risk factor that exacerbates COPD in urban environments.
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Background This study aimed to evaluate the association between the total suspended particles (TSP) generated from burning sugar cane plantations and the incidence of hospital admissions from hypertension in the city of Araraquara. Methods The study was an ecological time-series study. Total daily records of hypertension (ICD 10th I10-15) were obtained from admitted patients of all ages in a hospital in Araraquara, Sao Paulo State, Brazil, from 23 March 2003 to 27 July 2004. The daily concentration of TSP (mu g/m(3)) was obtained using a Handi-Vol sampler placed in downtown Araraquara. The local airport provided daily measures of temperature and humidity. In generalised linear Poisson regression models, the daily number of hospital admissions for hypertension was considered to be the dependent variable and the daily TSP concentration the independent variable. Results TSP presented a lagged effect on hypertension admissions, which was first observed 1 day after a TSP increase and remained almost unchanged for the following 2 days. A 10 mu g/m(3) increase in the TSP 3 day moving average lagged in 1 day led to an increase in hypertension-related hospital admissions during the harvest period (12.5%, 95% CI 5.6% to 19.9%) that was almost 30% higher than during non-harvest periods (9.0%, 95% CI 4.0% to 14.3%). Conclusions Increases in TSP concentrations were associated with hypertension-related hospital admissions. Despite the benefits of reduced air pollution in urban cities achieved by using ethanol produced from sugar cane to power automobiles, areas where the sugar cane is produced and harvested were found to have increased public health risk.
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Objectives: Air-pollution exposure has been associated with increased cardiovascular hospital admissions and mortality in time-series studies. We evaluated the relation between air pollutants and emergency room (ER) visits because of cardiac arrhythmia in a cardiology hospital. Methods: In a time-series study, we evaluated the association between the emergency room visits as a result of cardiac arrhythmia and daily variations in SO2, CO, NO2, O-3 and PM10, from January 1998 to August 1999. The cases of arrhythmia were modelled using generalised linear Poisson regression models, controlling for seasonality (short-term and long-term trend), and weather. Results: Interquartile range increases in CO (1.5 ppm), NO2 (49,5 mu g/m(3)) and PM10 (22.2 mu g/m(3)) on the concurrent day were associated with increases of 12.3% (95% CI: 7.6% to 17.2%), 10.4% (95% CI: 5.2% to 15.9%) and 6.7% (95% CI: 1.2% to 12.4%) in arrhythmia ER visits, respectively. PM10, CO and NO2 effects were dose-dependent and gaseous pollutants had thresholds. Only CO effect resisted estimates in models with more than one pollutant. Conclusions: Our results showed that air pollutant effects on arrhythmia are predominantly acute starting at concentrations below air quality standards, and the association with CO and NO2 suggests a relevant role for pollution caused by cars.
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In this paper, we present various diagnostic methods for polyhazard models. Polyhazard models are a flexible family for fitting lifetime data. Their main advantage over the single hazard models, such as the Weibull and the log-logistic models, is to include a large amount of nonmonotone hazard shapes, as bathtub and multimodal curves. Some influence methods, such as the local influence and total local influence of an individual are derived, analyzed and discussed. A discussion of the computation of the likelihood displacement as well as the normal curvature in the local influence method are presented. Finally, an example with real data is given for illustration.
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The economic occupation of an area of 500 ha for Piracicaba was studied with the irrigated cultures of maize, tomato, sugarcane and beans, having used models of deterministic linear programming and linear programming including risk for the Target-Motad model, where two situations had been analyzed. In the deterministic model the area was the restrictive factor and the water was not restrictive for none of the tested situations. For the first situation the gotten maximum income was of R$ 1,883,372.87 and for the second situation it was of R$ 1,821,772.40. In the model including risk a producer that accepts risk can in the first situation get the maximum income of R$ 1,883,372. 87 with a minimum risk of R$ 350 year(-1), and in the second situation R$ 1,821,772.40 with a minimum risk of R$ 40 year(-1). Already a producer averse to the risk can get in the first situation a maximum income of R$ 1,775,974.81 with null risk and for the second situation R$ 1.707.706, 26 with null risk, both without water restriction. These results stand out the importance of the inclusion of the risk in supplying alternative occupations to the producer, allowing to a producer taking of decision considered the risk aversion and the pretension of income.
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The objective of this work was to carry a descriptive analysis in the monthly precipitation of rainfall stations from Rio de Janeiro State, Brazil, using data of position and dispersion and graphical analyses, and to verify the presence of seasonality and trend in these data, with a study about the application of models of time series. The descriptive statistics was to characterize the general behavior of the series in three stations selected which present consistent historical series. The methodology of analysis of variance in randomized blocks and the determination of models of multiple linear regression, considering years and months as predictors variables, disclosed the presence of seasonality, what allowed to infer on the occurrence of repetitive natural phenomena throughout the time and absence of trend in the data. It was applied the methodology of multiple linear regression to removal the seasonality of these time series. The original data had been deducted from the estimates made by the adjusted model and the analysis of variance in randomized blocks for the residues of regression was preceded again. With the results obtained it was possible to conclude that the monthly rainfall present seasonality and they don`t present trend, the analysis of multiple regression was efficient in the removal of the seasonality, and the rainfall can be studied by means of time series.
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A significant problem in the collection of responses to potentially sensitive questions, such as relating to illegal, immoral or embarrassing activities, is non-sampling error due to refusal to respond or false responses. Eichhorn & Hayre (1983) suggested the use of scrambled responses to reduce this form of bias. This paper considers a linear regression model in which the dependent variable is unobserved but for which the sum or product with a scrambling random variable of known distribution, is known. The performance of two likelihood-based estimators is investigated, namely of a Bayesian estimator achieved through a Markov chain Monte Carlo (MCMC) sampling scheme, and a classical maximum-likelihood estimator. These two estimators and an estimator suggested by Singh, Joarder & King (1996) are compared. Monte Carlo results show that the Bayesian estimator outperforms the classical estimators in almost all cases, and the relative performance of the Bayesian estimator improves as the responses become more scrambled.
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It is recognized that vascular dispersion in the liver is a determinant of high first-pass extraction of solutes by that organ. Such dispersion is also required for translation of in-vitro microsomal activity into in-vivo predictions of hepatic extraction for any solute. We therefore investigated the relative dispersion of albumin transit times (CV2) in the livers of adult and weanling rats and in elasmobranch livers. The mean and normalized variance of the hepatic transit time distribution of albumin was estimated using parametric non-linear regression (with a correction for catheter influence) after an impulse (bolus) input of labelled albumin into a single-pass liver perfusion. The mean +/- s.e. of CV2 for albumin determined in each of the liver groups were 0.85 +/- 0.20 (n = 12), 1.48 +/- 0.33 (n = 7) and 0.90 +/- 0.18 (n = 4) for the livers of adult and weanling rats and elasmobranch livers, respectively. These CV2 are comparable with that reported previously for the dog and suggest that the CV2 Of the liver is of a similar order of magnitude irrespective of the age and morphological development of the species. It might, therefore, be justified, in the absence of other information, to predict the hepatic clearances and availabilities of highly extracted solutes by scaling within and between species livers using hepatic elimination models such as the dispersion model with a CV2 of approximately unity.
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A two-component survival mixture model is proposed to analyse a set of ischaemic stroke-specific mortality data. The survival experience of stroke patients after index stroke may be described by a subpopulation of patients in the acute condition and another subpopulation of patients in the chronic phase. To adjust for the inherent correlation of observations due to random hospital effects, a mixture model of two survival functions with random effects is formulated. Assuming a Weibull hazard in both components, an EM algorithm is developed for the estimation of fixed effect parameters and variance components. A simulation study is conducted to assess the performance of the two-component survival mixture model estimators. Simulation results confirm the applicability of the proposed model in a small sample setting. Copyright (C) 2004 John Wiley Sons, Ltd.
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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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The objective of this study was to estimate (co)variance functions using random regression models on Legendre polynomials for the analysis of repeated measures of BW from birth to adult age. A total of 82,064 records from 8,145 females were analyzed. Different models were compared. The models included additive direct and maternal effects, and animal and maternal permanent environmental effects as random terms. Contemporary group and dam age at calving (linear and quadratic effect) were included as fixed effects, and orthogonal Legendre polynomials of animal age (cubic regression) were considered as random co-variables. Eight models with polynomials of third to sixth order were used to describe additive direct and maternal effects, and animal and maternal permanent environmental effects. Residual effects were modeled using 1 (i.e., assuming homogeneity of variances across all ages) or 5 age classes. The model with 5 classes was the best to describe the trajectory of residuals along the growth curve. The model including fourth- and sixth-order polynomials for additive direct and animal permanent environmental effects, respectively, and third-order polynomials for maternal genetic and maternal permanent environmental effects were the best. Estimates of (co) variance obtained with the multi-trait and random regression models were similar. Direct heritability estimates obtained with the random regression models followed a trend similar to that obtained with the multi-trait model. The largest estimates of maternal heritability were those of BW taken close to 240 d of age. In general, estimates of correlation between BW from birth to 8 yr of age decreased with increasing distance between ages.
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The aim of the present study was to determine the relationship among body weight (BW), body condition score (BCS) and rump fat thickness (RFAT) measured by ultrasonography, and validate the relationship between BCS and RFAT over the time. Two hundred sixty and six Nelore cows had their BW, BCS and RFAT evaluated at five different moments during the production cycle: M1) weaning: M2) parturition, M3) 42 days post-partum; M4) 82 days postpartum and M5) 112 days post-partum. A BCS value was attributed for each cow following a I to 5 points scale. Ultrasonographic images for RFAT measurement were obtained using a 3.5 MHz linear transducer. Images were immediately analyzed as soon as they were formed and frozen. Body condition scores and ultrasound measurements were collected on the same day by a single trained technician. The relationship between BCS and RFAT values was investigated by regression models. The analysis of similarity among the five obtained models was performed using the proc MIXED from SAS and the correlations among variables were analyzed with proc CORR from SAS. The BCS was able to predict RFAT in Nelore cows in all different moments evaluated. Also, it was shown that BCS presented high correlation (r=0.82 to 0.93) and relationship (R(2) = 0.73 to 0.92) with RFAT. However, both BCS and RFAT showed low correlation (r=0.37 to 0.50) and relationship (R(2) = 0.13 to 0.25) with BW. The BCS classification by visual method using a 1 to 5 point scale, was able to predict the RFAT in Nelore cows over the time. (C) 2008 Elsevier B.V. All rights reserved.