A modified signed likelihood ratio test in elliptical structural models

In this paper we deal with the issue of performing accurate testing inference on a scalar parameter of interest in structural errors-in-variables models. The error terms are allowed to follow a multivariate distribution in the class of the elliptical distributions, which has the multivariate normal distribution as special case. We derive a modified signed likelihood ratio statistic that follows a standard normal distribution with a high degree of accuracy. Our Monte Carlo results show that the modified test is much less size distorted than its unmodified counterpart. An application is presented.

Bayesian estimation of regression parameters in elliptical measurement error models

The main object of this paper is to discuss the Bayes estimation of the regression coefficients in the elliptically distributed simple regression model with measurement errors. The posterior distribution for the line parameters is obtained in a closed form, considering the following: the ratio of the error variances is known, informative prior distribution for the error variance, and non-informative prior distributions for the regression coefficients and for the incidental parameters. We proved that the posterior distribution of the regression coefficients has at most two real modes. Situations with a single mode are more likely than those with two modes, especially in large samples. The precision of the modal estimators is studied by deriving the Hessian matrix, which although complicated can be computed numerically. The posterior mean is estimated by using the Gibbs sampling algorithm and approximations by normal distributions. The results are applied to a real data set and connections with results in the literature are reported. (C) 2011 Elsevier B.V. All rights reserved.

Skovgaard`s adjustment to likelihood ratio tests in exponential family nonlinear models

Likelihood ratio tests can be substantially size distorted in small- and moderate-sized samples. In this paper, we apply Skovgaard`s [Skovgaard, I.M., 2001. Likelihood asymptotics. Scandinavian journal of Statistics 28, 3-321] adjusted likelihood ratio statistic to exponential family nonlinear models. We show that the adjustment term has a simple compact form that can be easily implemented from standard statistical software. The adjusted statistic is approximately distributed as X(2) with high degree of accuracy. It is applicable in wide generality since it allows both the parameter of interest and the nuisance parameter to be vector-valued. Unlike the modified profile likelihood ratio statistic obtained from Cox and Reid [Cox, D.R., Reid, N., 1987. Parameter orthogonality and approximate conditional inference. journal of the Royal Statistical Society B49, 1-39], the adjusted statistic proposed here does not require an orthogonal parameterization. Numerical comparison of likelihood-based tests of varying dispersion favors the test we propose and a Bartlett-corrected version of the modified profile likelihood ratio test recently obtained by Cysneiros and Ferrari [Cysneiros, A.H.M.A., Ferrari, S.L.P., 2006. An improved likelihood ratio test for varying dispersion in exponential family nonlinear models. Statistics and Probability Letters 76 (3), 255-265]. (C) 2008 Elsevier B.V. All rights reserved.

Factors associated with increased prevalence of human papillomavirus infection in a cohort of HIV-Infected Brazilian women

Objectives: Human papillomavirus (HPV) infection is a major risk factor for cervical disease. Using baseline data from the HIV-infected cohort of Evandro Chagas Clinical Research Institute at Fiocruz, Rio de Janeiro, Brazil, factors associated with an increased prevalence of HPV were assessed. Methods: Samples from 634 HIV-infected women were tested for the presence of HPV infection using hybrid capture 11 and polymerase chain reaction. Prevalence ratios (PR) were estimated using Poisson regression analysis with robust variance. Results: The overall prevalence of HPV infection was 48%, of which 94% were infected with a high-risk HPV. In multivariate analysis, factors independently associated with infection with high-risk HPV type were: younger age (<30 years of age; PR 1.5, 95% confidence interval (CI) 1.1-2.1), current or prior drug use (PR 1.3, 95% CI 1.0-1.6), self-reported history of HPV infection (PR 1.2, 95% CI 0.96-1.6), condom use in the last sexual intercourse (PR 1.3, 95% CI 1.1-1.7), and nadir CD4+ T-cell count <100 cells/mm(3) (PR 1.6, 95% CI 1.2-2.1). Conclusions: The estimated prevalence of high-risk HPV-infection among HIV-infected women from Rio de Janeiro, Brazil, was high. Close monitoring of HPV-related effects is warranted in all HIV-infected women, in particular those of younger age and advanced immunosuppression. (C) 2008 International Society for Infectious Diseases. Published by Elsevier Ltd. All rights reserved.

A fast and robust statistical test based on likelihood ratio with Bartlett correction to identify Granger causality between gene sets

We propose a likelihood ratio test ( LRT) with Bartlett correction in order to identify Granger causality between sets of time series gene expression data. The performance of the proposed test is compared to a previously published bootstrapbased approach. LRT is shown to be significantly faster and statistically powerful even within non- Normal distributions. An R package named gGranger containing an implementation for both Granger causality identification tests is also provided.

Prigogine-Defay Ratio for an Ionic Glass-Former: Molecular Dynamics Simulations

The pressure dependence of the glass-transition temperature, T(g)(P), of the ionic glass-former 2Ca(NO(3))(2) center dot 3KNO(3), CKN, has been obtained by molecular dynamics (MD) simulations The liquid-glass difference of thermal expansivity, Delta alpha, heat capacity, Delta C(p), and isothermal compressibility, Delta kappa, have been calculated as a function of pressure. It has been found that the Ehrenfest relation dT(g)/dP = TV Delta alpha/Delta C(p) predicts the pressure dependence of T, but the other Ehrenfest relation, dT(g)/dP = Delta kappa/Delta alpha, does not. Consequently, the Prigogine-Defay ratio, Pi = Delta C(p)Delta kappa/TV Delta alpha(2), is Pi similar to 1.2 at low pressures, but increases 1 order of magnitude at high pressures. The pressure dependence of the Prigogine-Defay ratio is interpreted in light of recent explanations for the finding Pi > 1.