965 resultados para joint hypothesis tests
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Se realizó un estudio genético – poblacional en dos grupos etarios de población colombiana con la finalidad de evaluar las diferencias genéticas relacionadas con el polimorfismo MTHFR 677CT en busca de eventos genéticos que soporten la persistencia de este polimorfismo en la especie humana debido que este ha sido asociado con múltiples enfermedades. De esta manera se genotipificaron los individuos, se analizaron los genotipos, frecuencias alélicas y se realizaron diferentes pruebas genéticas-poblacionales. Contrario a lo observado en poblaciones Colombianas revisadas se identificó la ausencia del Equilibrio Hardy-Weinberg en el grupo de los niños y estructuras poblacionales entre los adultos lo que sugiere diferentes historias demográficas y culturales entre estos dos grupos poblacionales al tiempo, lo que soporta la hipótesis de un evento de selección sobre el polimorfismo en nuestra población. De igual manera nuestros datos fueron analizados junto con estudios previos a nivel nacional y mundial lo cual sustenta que el posible evento selectivo es debido a que el aporte de ácido fólico se ha incrementado durante las últimas dos décadas como consecuencia de las campañas de fortificación de las harinas y suplementación a las embarazadas con ácido fólico, por lo tanto aquí se propone un modelo de selección que se ajusta a los datos encontrados en este trabajo se establece una relación entre los patrones nutricionales de la especie humana a través de la historia que explica las diferencias en frecuencias de este polimorfismo a nivel espacial y temporal.
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1. Chemical effects on organisms are typically assessed using individual-level endpoints or sometimes population growth rate (PGR), but such measurements are generally made at low population densities. In contrast most natural populations are subject to density dependence and fluctuate around the environmental carrying capacity as a result of individual competition for resources. As ecotoxicology aims to make reliable population projections of chemical impacts in the field, an understanding of how high-density or resource-limited populations respond to environmental chemicals is essential. 2. Our objective was to determine the joint effects of population density and chemical stress on the life history and PGR of an important ecotoxicological indicator species, Chironomus riparius, under controlled laboratory conditions. Populations were fed the same ration but initiated at different densities and exposed to a solvent control and three concentrations of C-14-cypermethrin in a sediment-water test system for 67 days at 20 +/- 1 degreesC. 3. Density had a negative effect on all the measured life-history traits, and PGR declined with increasing density in the controls. Exposure to C-14-cypermethrin had a direct negative effect on juvenile survival, presumably within the first 24 h because the chemical rapidly dissipated from the water column. Reductions in the initial larval densities resulted in an increase in the available resources for the survivors. Subsequently, exposed populations emerged sooner and started producing offspring earlier than the controls. C-14-cypermethrin had no effect on estimated fecundity and adult body weight but interacted with density to reduce the time to first emergence and first reproduction. As a result, PGR increased with cypermethrin concentration when populations were initiated at high densities. 4. Synthesis and applications. The results showed that the effects of C-14-cypermethrin were buffered at high density, so that the joint effects of density and chemical stress on PGR were less than additive. Low levels of chemical stressors may increase carrying capacity by reducing juvenile competition for resources. More and perhaps fitter adults may be produced, similar to the effects of predators and culling; however, toxicant exposure may result in survivors that are less tolerant to changing conditions. If less than additive effects are typical in the field, standard regulatory tests carried out at low density may overestimate the effects of environmental chemicals. Further studies over a wide range of chemical stressors and organisms with contrasting life histories are needed to make general recommendations.
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A situation assessment uses reports from sensors to produce hypotheses about a situation at a level of aggregation that is of direct interest to a military commander. A low level of aggregation could mean forming tracks from reports, which is well documented in the tracking literature as track initiation and data association. In this paper there is also discussion on higher level aggregation; assessing the membership of tracks to larger groups. Ideas used in joint tracking and identification are extended, using multi-entity Bayesian networks to model a number of static variables, of which the identity of a target is one. For higher level aggregation a scheme for hypothesis management is required. It is shown how an offline clustering of vehicles can be reduced to an assignment problem.
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We investigate for 26 OECD economies whether their current account imbalances to GDP are driven by stochastic trends. Regarding bounded stationarity as the more natural counterpart of sustainability, results from Phillips–Perron tests for unit root and bounded unit root processes are contrasted. While the former hint at stationarity of current account imbalances for 12 economies, the latter indicate bounded stationarity for only six economies. Through panel-based test statistics, current account imbalances are diagnosed as bounded non-stationary. Thus, (spurious) rejections of the unit root hypothesis might be due to the existence of bounds reflecting hidden policy controls or financial crises.
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The main purpose of this work is to study the behaviour of Skovgaard`s [Skovgaard, I.M., 2001. Likelihood asymptotics. Scandinavian journal of Statistics 28, 3-32] adjusted likelihood ratio statistic in testing simple hypothesis in a new class of regression models proposed here. The proposed class of regression models considers Dirichlet distributed observations, and the parameters that index the Dirichlet distributions are related to covariates and unknown regression coefficients. This class is useful for modelling data consisting of multivariate positive observations summing to one and generalizes the beta regression model described in Vasconcellos and Cribari-Neto [Vasconcellos, K.L.P., Cribari-Neto, F., 2005. Improved maximum likelihood estimation in a new class of beta regression models. Brazilian journal of Probability and Statistics 19,13-31]. We show that, for our model, Skovgaard`s adjusted likelihood ratio statistics have a simple compact form that can be easily implemented in standard statistical software. The adjusted statistic is approximately chi-squared distributed with a high degree of accuracy. Some numerical simulations show that the modified test is more reliable in finite samples than the usual likelihood ratio procedure. An empirical application is also presented and discussed. (C) 2009 Elsevier B.V. All rights reserved.
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In this essay, a method for comparing the asymptotic power of the multivariate unit root tests proposed in Phillips & Durlauf (1986) and Flˆores, Preumont & Szafarz (1996) is proposed. In order to determine the asymptotic power of the tests the asymptotic distributions under the null hypothesis and under the set of alternative hypotheses described in Phillips (1988) are determined. In addition, a test which combines characteristics of both tests is proposed and its distributions under the null hypothesis and the same set of alternative hypotheses are determined. This allows us to determine what causes any difference in the asymptotic power of the two tests against the set of alternative hypotheses considered
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Empirical evidence suggests that real exchange rate is characterized by the presence of near-unity and additive outliers. Recent studeis have found evidence on favor PPP reversion by using the quasi-differencing (Elliott et al., 1996) unit root tests (ERS), which is more efficient against local alternatives but is still based on least squares estimation. Unit root tests basead on least saquares method usually tend to bias inference towards stationarity when additive out liers are present. In this paper, we incorporate quasi-differencing into M-estimation to construct a unit root test that is robust not only against near-unity root but also against nonGaussian behavior provoked by assitive outliers. We re-visit the PPP hypothesis and found less evidemce in favor PPP reversion when non-Gaussian behavior in real exchange rates is taken into account.
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This paper investigates the presence of long memory in financiaI time series using four test statistics: V/S, KPSS, KS and modified R/S. There has been a large amount of study on the long memory behavior in economic and financiaI time series. However, there is still no consensus. We argue in this paper that spurious short-term memory may be found due to the incorrect use of data-dependent bandwidth to estimating the longrun variance. We propose a partially adaptive lag truncation procedure that is robust against the presence of long memory under the alternative hypothesis and revisit several economic and financiaI time series using the proposed bandwidth choice. Our results indicate the existence of spurious short memory in real exchange rates when Andrews' formula is employed, but long memory is detected when the proposed lag truncation procedure is used. Using stock market data, we also found short memory in returns and long memory in volatility.
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This paper develops nonparametric tests of independence between two stationary stochastic processes. The testing strategy boils down to gauging the closeness between the joint and the product of the marginal stationary densities. For that purpose, I take advantage of a generalized entropic measure so as to build a class of nonparametric tests of independence. Asymptotic normality and local power are derived using the functional delta method for kernels, whereas finite sample properties are investigated through Monte Carlo simulations.
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This dissertation deals with the problem of making inference when there is weak identification in models of instrumental variables regression. More specifically we are interested in one-sided hypothesis testing for the coefficient of the endogenous variable when the instruments are weak. The focus is on the conditional tests based on likelihood ratio, score and Wald statistics. Theoretical and numerical work shows that the conditional t-test based on the two-stage least square (2SLS) estimator performs well even when instruments are weakly correlated with the endogenous variable. The conditional approach correct uniformly its size and when the population F-statistic is as small as two, its power is near the power envelopes for similar and non-similar tests. This finding is surprising considering the bad performance of the two-sided conditional t-tests found in Andrews, Moreira and Stock (2007). Given this counter intuitive result, we propose novel two-sided t-tests which are approximately unbiased and can perform as well as the conditional likelihood ratio (CLR) test of Moreira (2003).
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This paper considers two-sided tests for the parameter of an endogenous variable in an instrumental variable (IV) model with heteroskedastic and autocorrelated errors. We develop the nite-sample theory of weighted-average power (WAP) tests with normal errors and a known long-run variance. We introduce two weights which are invariant to orthogonal transformations of the instruments; e.g., changing the order in which the instruments appear. While tests using the MM1 weight can be severely biased, optimal tests based on the MM2 weight are naturally two-sided when errors are homoskedastic. We propose two boundary conditions that yield two-sided tests whether errors are homoskedastic or not. The locally unbiased (LU) condition is related to the power around the null hypothesis and is a weaker requirement than unbiasedness. The strongly unbiased (SU) condition is more restrictive than LU, but the associated WAP tests are easier to implement. Several tests are SU in nite samples or asymptotically, including tests robust to weak IV (such as the Anderson-Rubin, score, conditional quasi-likelihood ratio, and I. Andrews' (2015) PI-CLC tests) and two-sided tests which are optimal when the sample size is large and instruments are strong. We refer to the WAP-SU tests based on our weights as MM1-SU and MM2-SU tests. Dropping the restrictive assumptions of normality and known variance, the theory is shown to remain valid at the cost of asymptotic approximations. The MM2-SU test is optimal under the strong IV asymptotics, and outperforms other existing tests under the weak IV asymptotics.
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In this work we focus on tests for the parameter of an endogenous variable in a weakly identi ed instrumental variable regressionmodel. We propose a new unbiasedness restriction for weighted average power (WAP) tests introduced by Moreira and Moreira (2013). This new boundary condition is motivated by the score e ciency under strong identi cation. It allows reducing computational costs of WAP tests by replacing the strongly unbiased condition. This latter restriction imposes, under the null hypothesis, the test to be uncorrelated to a given statistic with dimension given by the number of instruments. The new proposed boundary condition only imposes the test to be uncorrelated to a linear combination of the statistic. WAP tests under both restrictions to perform similarly numerically. We apply the di erent tests discussed to an empirical example. Using data from Yogo (2004), we assess the e ect of weak instruments on the estimation of the elasticity of inter-temporal substitution of a CCAPM model.
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Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)
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Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)
Muscle strength assessment among children and adolescents with growing pains and joint hypermobility
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OBJETIVO: Avaliar, por meio de teste quantitativo, a força muscular em crianças e adolescentes com dores de crescimento, associada ou não com hipermobilidade articular e comparadas com controles saudáveis. MÉTODO: Quarenta e sete casos de crianças e adolescentes acompanhados por dores de crescimento, sendo 24 com hipermobilidade articular (DC-HA), 23 sem hipermobilidade articular (DC) e 47 controles saudáveis pareados por idade e gênero foram submetidos a dois testes quantitativos para a avaliação da força muscular, o Childhood Myositis Assessment Scale (CMAS) e o Manual Muscle Strength Test (MMT). Os dados antropométricos como altura, peso, índice de massa corporal, prega cutânea tricipital, circunferência média do braço e a área muscular do braço foram comparados entre os três grupos. RESULTADOS: Os três grupos não apresentaram diferença estatística entre as medidas antropométricas. Houve diferença significante entre a mediana da pontuação do CMAS, sendo menores no grupo DC (47, mínimo e máximo 39-52) e DC-HA (46, mínimo e máximo 40-51), comparados com controles (50, mínimo e máximo 45-52; p<0,0001). Dois dos exercícios cronometrados do CMAS, a elevação da cabeça e a duração da elevação das pernas, tiveram menor pontuação nos pacientes comparados aos controles (p<0.0001). A pontuação mediana do MMT no grupo DC (79, mínimo e máximo 73-80) e DC-HA (78, mínimo e máximo 32-80) também apresentou diferença significante, sendo menor nos pacientes que nos controles (80, mínimo e máximo 78-80; p<0,0001). A melhor correlação entre a pontuação do CMAS e MMT foi no grupo DC-HA (Spearman r=0,65; p=0,0007). A aplicação do CMAS e MMT em duas ocasiões apresentou boa concordância e coeficiente de correlação intraclasse de 0,87 (IC 95% 0,64-0,96; p<0,0001) e 0,92 (IC 95% 0,76-0,97; p<0,0001), respectivamente. CONCLUSÃO: Os pacientes com dores de crescimento com ou sem hipermobilidade articular apresentaram fraqueza muscular de leve a moderada quando comparados com controles saudáveis.