165 resultados para Modified signed likelihood ratio statistic
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O presente trabalho avaliou a variabilidade amostral dos parâmetros da distribuição gama, relativos a séries mensais de precipitação pluvial, nas regiões de Campinas-SP e Pelotas-RS, que têm dados para os períodos de 1890-2006 e 1890-2005, respectivamente. Assim, os espaços amostrais considerados foram de 58, 39 e 29 anos para Campinas e 58 e 29 anos para Pelotas. As análises foram feitas usando o teste da razão da máxima verossimilhança. Os resultados apontaram significativas alterações amostrais. Não houve indicações de tendências contínuas (redução ou aumento) no regime mensal de precipitação pluvial na região de Campinas-SP. Em contrapartida, esse teste indicou, para a localidade de Pelotas-RS, tendência de elevação no regime desse elemento meteorológico ocorrida entre as amostras relativas aos anos de 1948 a 1976 e 1977 a 2005.
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OBJETIVO: Analisar a prevalência da infecção genital por papilomavírus humano (HPV) de alto risco por faixa etária e fatores associados. MÉTODOS: Estudo transversal com amostra de 2.300 mulheres (15-65 anos) que buscaram rastreamento para o câncer cervical entre fevereiro de 2002 e março de 2003 em São Paulo e Campinas, estado de São Paulo. Aplicou-se questionário epidemiológico e realizou-se coleta cervical para citologia oncológica e teste de captura híbrida II. As análises estatísticas empregadas foram teste de qui-quadrado de Pearson e análise multivariada pelo método forward likelihood ratio. RESULTADOS: A prevalência total da infecção genital por HPV de alto risco foi de 17,8%, distribuída nas faixas etárias: 27,1% (<25 anos), 21,3% (25-34 anos), 12,1% (35-44 anos), 12,0% (45-54 anos) e de 13,9% (55-65 anos). Participantes com maior número de parceiros sexuais durante a vida apresentaram maior freqüência da infecção. Relacionamento estável, idade de 35 a 44 anos e ex-fumantes foram associados à proteção da infecção. A infecção genital por HPV de alto risco ocorreu em 14,3% das citologias normais, em 77,8% das lesões escamosas de alto grau e nos dois (100%) casos de carcinoma. CONCLUSÕES: A prevalência da infecção genital por HPV de alto risco na amostra estudada foi alta. Houve predomínio de casos abaixo dos 25 anos e tendência a um novo aumento após os 55 anos, com maior freqüência naqueles com maior número de parceiros sexuais durante a vida
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The effect of genetic and non-genetic factors for carcass, breast meat and leg weights, and yields of a commercial broiler line were investigated using the restricted maximum likelihood method, considering four different animal models, including or excluding maternal genetic effect with covariance between direct and maternal genetic effects, and maternal permanent environmental effect. The likelihood ratio test was used to determine the most adequate model for each trait. For carcass, breast, and leg weight, and for carcass and breast yield, maternal genetic and permanent environmental effects as well as the covariance between direct and maternal genetic effects were significant. The estimates of direct and maternal heritability were 0.17 and 0.04 for carcass weight, 0.26 and 0.06 for breast weight, 0.22 and 0.02 for leg weight, 0.32 and 0.02 for carcass yield, and 0.52 and 0.04 for breast yield, respectively. For leg yield, maternal permanent environmental effect was important, in addition to direct genetic effects. For that trait, direct heritability and maternal permanent environmental variance as a proportion of the phenotypic variance were 0.43 and 0.02, respectively. The results indicate that ignoring maternal effects in the models, even though they were of small magnitude (0.02 to 0.06), tended to overestimate direct genetic variance and heritability for all traits.
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Background: Severe outcomes have been described for both Plasmodium falciparum and P. vivax infections. The identification of sensitive and reliable markers of disease severity is fundamental to improving patient care. An intense pro-inflammatory response with oxidative stress and production of reactive oxygen species is present in malaria. Inflammatory cytokines such as tumor necrosis factor-alpha (TNF-alpha) and antioxidant agents such as superoxide dismutase-1 (SOD-1) are likely candidate biomarkers for disease severity. Here we tested whether plasma levels of SOD-1 could serve as a biomarker of severe vivax malaria. Methodology/Principal Findings: Plasma samples were obtained from residents of the Brazilian Amazon with a high risk for P. vivax transmission. Malaria diagnosis was made by both microscopy and nested PCR. A total of 219 individuals were enrolled: non-infected volunteers (n = 90) and individuals with vivax malaria: asymptomatic (n = 60), mild (n = 50) and severe infection (n = 19). SOD-1 was directly associated with parasitaemia, plasma creatinine and alanine amino-transaminase levels, while TNF-alpha correlated only with the later enzyme. The predictive power of SOD-1 and TNF-alpha levels was compared. SOD-1 protein levels were more effective at predicting vivax malaria severity than TNF-alpha. For discrimination of mild infection, elevated SOD-1 levels showed greater sensitivity than TNF-alpha (76% vs. 30% respectively; p < 0.0001), with higher specificity (100% vs. 97%; p < 0.0001). In predicting severe vivax malaria, SOD-1 levels exhibited higher sensitivity than TNF-alpha (80% vs. 56%, respectively; p < 0.0001; likelihood ratio: 7.45 vs. 3.14; p, 0.0001). Neither SOD-1 nor TNF-alpha could discriminate P. vivax infections from those caused by P. falciparum. Conclusion: SOD-1 is a powerful predictor of disease severity in individuals with different clinical presentations of vivax malaria.
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Background: Despite governmental and private efforts on providing malaria control, this disease continues to be a major health threat. Thus, innovative strategies are needed to reduce disease burden. The malaria vectors, through the injection of saliva into the host skin, play important role on disease transmission and may influence malaria morbidity. This study describes the humoral immune response against Anopheles (An.) darlingi saliva in volunteers from the Brazilian Amazon and addresses the association between levels of specific antibodies and clinical presentation of Plasmodium (P.) vivax infection. Methods: Adult volunteers from communities in the Rondonia State, Brazil, were screened in order to assess the presence of P. vivax infection by light microscopy and nested PCR. Non-infected volunteers and individuals with symptomatic or symptomless infection were randomly selected and plasma collected. An. darlingi salivary gland sonicates (SGS) were prepared and used to measure anti-saliva antibody levels. Plasma interleukin (IL)-10 and interferon (IFN)-gamma levels were also estimated and correlated to anti-SGS levels. Results: Individuals infected with P. vivax presented higher levels of anti-SGS than non-infected individuals and antibody levels could discriminate infection. Furthermore, anti-saliva antibody measurement was also useful to distinguish asymptomatic infection from non-infection, with a high likelihood ratio. Interestingly, individuals with asymptomatic parasitaemia presented higher titers of anti-SGS and lower IFN-gamma/IL-10 ratio than symptomatic ones. In P. vivax-infected asymptomatic individuals, the IFN-gamma/IL-10 ratio was inversely correlated to anti-SGS titers, although not for while in symptomatic volunteers. Conclusion: The estimation of anti-An. darlingi antibody levels can indicate the probable P. vivax infection status and also could serve as a marker of disease severity in this region of Brazilian Amazon.
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This article presents maximum likelihood estimators (MLEs) and log-likelihood ratio (LLR) tests for the eigenvalues and eigenvectors of Gaussian random symmetric matrices of arbitrary dimension, where the observations are independent repeated samples from one or two populations. These inference problems are relevant in the analysis of diffusion tensor imaging data and polarized cosmic background radiation data, where the observations are, respectively, 3 x 3 and 2 x 2 symmetric positive definite matrices. The parameter sets involved in the inference problems for eigenvalues and eigenvectors are subsets of Euclidean space that are either affine subspaces, embedded submanifolds that are invariant under orthogonal transformations or polyhedral convex cones. We show that for a class of sets that includes the ones considered in this paper, the MLEs of the mean parameter do not depend on the covariance parameters if and only if the covariance structure is orthogonally invariant. Closed-form expressions for the MLEs and the associated LLRs are derived for this covariance structure.
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Marker assisted selection depends on the identification of tightly linked association between marker and the trait of interest. In the present work, functional (EST-SSRs) and genomic (gSSRs) microsatellite markers were used to detect putative QTLs for sugarcane yield components (stalk number, diameter and height) and as well as for quality parameters (Brix, Pol and fibre) in plant cane. The mapping population (200 individuals) was derived from a bi-parental cross (IACSP95-3018 x IACSP93-3046) from the IAC Sugarcane Breeding Program. As the map is under construction, single marker trait association analysis based on the likelihood ratio test was undertaken to detect the QTLs. Of the 215 single dose markers evaluated (1:1 and 3:1), 90 (42%) were associated with putative QTLs involving 43 microsatellite primers (18 gSSRs and 25 EST-SSRs). For the yield components, 41 marker/trait associations were found: 20 for height, 6 for diameter and 15 for stalk number. An EST-SSRs marker with homology to non-phototropic hypocotyls 4 (NPH4) protein was associated with a putative QTL with positive effect for diameter as also with a negative effect for stalk number. In relation to the quality parameters, 18 marker trait associations were found for Brix, 19 for Pol, and 12 for fibre. For fibre, 58% of the QTLs detected showed a negative effect on this trait. Some makers associated with QTLs with a negative effect for fibre showed a positive effect for Pol, reflecting the negative correlation generally observed between these traits.
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Background: The presence of coronary artery calcium (CAC) is an independent marker of increased risk of cardiovascular disease (CVD) events and mortality. However, the predictive value of thoracic aorta calcification (TAC), which can be additionally identified without further scanning during assessment of CAC, is unknown. Methods: We followed a cohort of 8401 asymptomatic individuals (mean age: 53 +/- 10 years, 69% men) undergoing cardiac risk factor evaluation and TAC and CAC testing with electron beam computed tomography. Multivariable Cox proportional hazards models were developed to predict all-cause mortality based on the presence of TAC. Results: During a median follow-up period of 5 years, 124 (1.5%) deaths were observed. Overall survival was 96.9% and 98.9% for those with and without detectable TAC, respectively (p < 0.0001). Compared to those with no TAC, the hazard ratio for mortality in the presence of TAC was 3.25 (95% CI: 2.28-4.65, p < 0.0001) in unadjusted analysis. After adjusting for age, gender, hypertension, dyslipidemia, diabetes mellitus, smoking and family history of premature coronary artery disease, and presence of CAC the relationship remained robust (HR 1.61, 95% CI: 1.10-2.27, p = 0.015). Likelihood ratio chi(2) statistics demonstrated that the addition of TAC contributed significantly in predicting mortality to traditional risk factors alone (chi(2) = 13.62, p = 0.002) as well as risk factors + CAC (chi(2) = 5.84, p = 0.02) models. Conclusion: In conclusion, the presence of TAC was associated with all-cause mortality in our study; this relationship was independent of conventional CVD risk factors as well as the presence of CAC. (C) 2009 Elsevier Ireland Ltd. All rights reserved.
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Aortic valve calcium (AVC) can be quantified on the same computed tomographic scan as coronary artery calcium (CAC). Although CAC is an established predictor of cardiovascular events, limited evidence is available for an independent predictive value for AVC. We studied a cohort of 8,401 asymptomatic subjects (mean age 53 10 years, 69% men), who were free of known coronary heart disease and were undergoing electron beam computed tomography for assessment of subclinical atherosclerosis. The patients were followed for a median of 5 years (range 1 to 7) for the occurrence of mortality from any cause. Multivariate Cox regression models were developed to predict all-cause mortality according to the presence of AVC. A total of 517 patients (6%) had AVC on electron beam computed tomography. During follow-up, 124 patients died (1.5%), for an overall survival rate of 96.1% and 98.7% for those with and without AVC, respectively (hazard ratio 3.39, 95% confidence interval 2.09 to 5.49). After adjustment for age, gender, hypertension, dyslipidemia, diabetes mellitus, smoking, and a family history of premature coronary heart disease, AVC remained a significant predictor of mortality (hazard ratio 1.82, 95% confidence interval 1.11 to 2.98). Likelihood ratio chi-square statistics demonstrated that the addition of AVC contributed significantly to the prediction of mortality in a model adjusted for traditional risk factors (chi-square = 5.03, p = 0.03) as well as traditional risk factors plus the presence of CAC (chi-square = 3.58, p = 0.05). In conclusion, AVC was associated with increased all-cause mortality, independent of the traditional risk factors and the presence of CAC. (C) 2010 Published by Elsevier Inc. (Am J Cardiol 2010;106:1787-1791)
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Background. The am of this study was to determine the predictive value for malignancy of microcalcifications determined by ultrasonography in thyroid nodules. Methods. One hundred seventy-seven nodules were prospectively studied by ultrasonography and compared with their fine-needle aspirative biopsy. The association between the presence and type of calcification and cytologic findings was verified through the chi-square test or likelihood ratio. Results. Thirty nodules showed calcification, of which 17 had fine calcifications, 3 had fine and gross calcifications, and 10 had only coarse calcification. Seven (41.18%) of 17 fine calcified nodules were malignant on cytology, 8 (47.06%) were benign, 1 (5,88%) was indeterminate, and 1 was suspect for malignancy. We found statistical significance between the presence of fine calcifications and malignancy (p =.001) and, in the 13 malignant nodule group, 8 (61.50%) had fine calcifications. Conclusion. This study suggests that microcalcifications were highly specific for malignancy and were present in 61% of the malignant nodules. (c) 2008 Wiley Periodicals, Inc.
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The estimation of data transformation is very useful to yield response variables satisfying closely a normal linear model, Generalized linear models enable the fitting of models to a wide range of data types. These models are based on exponential dispersion models. We propose a new class of transformed generalized linear models to extend the Box and Cox models and the generalized linear models. We use the generalized linear model framework to fit these models and discuss maximum likelihood estimation and inference. We give a simple formula to estimate the parameter that index the transformation of the response variable for a subclass of models. We also give a simple formula to estimate the rth moment of the original dependent variable. We explore the possibility of using these models to time series data to extend the generalized autoregressive moving average models discussed by Benjamin er al. [Generalized autoregressive moving average models. J. Amer. Statist. Assoc. 98, 214-223]. The usefulness of these models is illustrated in a Simulation study and in applications to three real data sets. (C) 2009 Elsevier B.V. All rights reserved.
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We introduce in this paper a new class of discrete generalized nonlinear models to extend the binomial, Poisson and negative binomial models to cope with count data. This class of models includes some important models such as log-nonlinear models, logit, probit and negative binomial nonlinear models, generalized Poisson and generalized negative binomial regression models, among other models, which enables the fitting of a wide range of models to count data. We derive an iterative process for fitting these models by maximum likelihood and discuss inference on the parameters. The usefulness of the new class of models is illustrated with an application to a real data set. (C) 2008 Elsevier B.V. All rights reserved.
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The use of inter-laboratory test comparisons to determine the performance of individual laboratories for specific tests (or for calibration) [ISO/IEC Guide 43-1, 1997. Proficiency testing by interlaboratory comparisons - Part 1: Development and operation of proficiency testing schemes] is called Proficiency Testing (PT). In this paper we propose the use of the generalized likelihood ratio test to compare the performance of the group of laboratories for specific tests relative to the assigned value and illustrate the procedure considering an actual data from the PT program in the area of volume. The proposed test extends the test criteria in use allowing to test for the consistency of the group of laboratories. Moreover, the class of elliptical distributions are considered for the obtained measurements. (C) 2008 Elsevier B.V. All rights reserved.
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The Birnbaum-Saunders distribution has been used quite effectively to model times to failure for materials subject to fatigue and for modeling lifetime data. In this paper we obtain asymptotic expansions, up to order n(-1/2) and under a sequence of Pitman alternatives, for the non-null distribution functions of the likelihood ratio, Wald, score and gradient test statistics in the Birnbaum-Saunders regression model. The asymptotic distributions of all four statistics are obtained for testing a subset of regression parameters and for testing the shape parameter. Monte Carlo simulation is presented in order to compare the finite-sample performance of these tests. We also present two empirical applications. (C) 2010 Elsevier B.V. All rights reserved.
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In this article, we deal with the issue of performing accurate small-sample inference in the Birnbaum-Saunders regression model, which can be useful for modeling lifetime or reliability data. We derive a Bartlett-type correction for the score test and numerically compare the corrected test with the usual score test and some other competitors.