Bayesian analysis of skew-t multivariate null intercept measurement error model

The multivariate skew-t distribution (J Multivar Anal 79:93-113, 2001; J R Stat Soc, Ser B 65:367-389, 2003; Statistics 37:359-363, 2003) includes the Student t, skew-Cauchy and Cauchy distributions as special cases and the normal and skew-normal ones as limiting cases. In this paper, we explore the use of Markov Chain Monte Carlo (MCMC) methods to develop a Bayesian analysis of repeated measures, pretest/post-test data, under multivariate null intercept measurement error model (J Biopharm Stat 13(4):763-771, 2003) where the random errors and the unobserved value of the covariate (latent variable) follows a Student t and skew-t distribution, respectively. The results and methods are numerically illustrated with an example in the field of dentistry.

Hypotheses Testing on a Multivariate Null Intercept Errors-in-Variables Model

Considering the Wald, score, and likelihood ratio asymptotic test statistics, we analyze a multivariate null intercept errors-in-variables regression model, where the explanatory and the response variables are subject to measurement errors, and a possible structure of dependency between the measurements taken within the same individual are incorporated, representing a longitudinal structure. This model was proposed by Aoki et al. (2003b) and analyzed under the bayesian approach. In this article, considering the classical approach, we analyze asymptotic test statistics and present a simulation study to compare the behavior of the three test statistics for different sample sizes, parameter values and nominal levels of the test. Also, closed form expressions for the score function and the Fisher information matrix are presented. We consider two real numerical illustrations, the odontological data set from Hadgu and Koch (1999), and a quality control data set.

Bayesian analysis for a skew extension of the multivariate null intercept measurement error model

Skew-normal distribution is a class of distributions that includes the normal distributions as a special case. In this paper, we explore the use of Markov Chain Monte Carlo (MCMC) methods to develop a Bayesian analysis in a multivariate, null intercept, measurement error model [R. Aoki, H. Bolfarine, J.A. Achcar, and D. Leao Pinto Jr, Bayesian analysis of a multivariate null intercept error-in -variables regression model, J. Biopharm. Stat. 13(4) (2003b), pp. 763-771] where the unobserved value of the covariate (latent variable) follows a skew-normal distribution. The results and methods are applied to a real dental clinical trial presented in [A. Hadgu and G. Koch, Application of generalized estimating equations to a dental randomized clinical trial, J. Biopharm. Stat. 9 (1999), pp. 161-178].

Inference and local influence assessment in skew-normal null intercept measurement error model

In this article, we discuss inferential aspects of the measurement error regression models with null intercepts when the unknown quantity x (latent variable) follows a skew normal distribution. We examine first the maximum-likelihood approach to estimation via the EM algorithm by exploring statistical properties of the model considered. Then, the marginal likelihood, the score function and the observed information matrix of the observed quantities are presented allowing direct inference implementation. In order to discuss some diagnostics techniques in this type of models, we derive the appropriate matrices to assessing the local influence on the parameter estimates under different perturbation schemes. The results and methods developed in this paper are illustrated considering part of a real data set used by Hadgu and Koch [1999, Application of generalized estimating equations to a dental randomized clinical trial. Journal of Biopharmaceutical Statistics, 9, 161-178].

Hypothesis testing in an errors-in-variables model with heteroscedastic measurement errors

In many epidemiological studies it is common to resort to regression models relating incidence of a disease and its risk factors. The main goal of this paper is to consider inference on such models with error-prone observations and variances of the measurement errors changing across observations. We suppose that the observations follow a bivariate normal distribution and the measurement errors are normally distributed. Aggregate data allow the estimation of the error variances. Maximum likelihood estimates are computed numerically via the EM algorithm. Consistent estimation of the asymptotic variance of the maximum likelihood estimators is also discussed. Test statistics are proposed for testing hypotheses of interest. Further, we implement a simple graphical device that enables an assessment of the model`s goodness of fit. Results of simulations concerning the properties of the test statistics are reported. The approach is illustrated with data from the WHO MONICA Project on cardiovascular disease. Copyright (C) 2008 John Wiley & Sons, Ltd.

A robust Bayesian approach to null intercept measurement error model with application to dental data

Measurement error models often arise in epidemiological and clinical research. Usually, in this set up it is assumed that the latent variable has a normal distribution. However, the normality assumption may not be always correct. Skew-normal/independent distribution is a class of asymmetric thick-tailed distributions which includes the Skew-normal distribution as a special case. In this paper, we explore the use of skew-normal/independent distribution as a robust alternative to null intercept measurement error model under a Bayesian paradigm. We assume that the random errors and the unobserved value of the covariate (latent variable) follows jointly a skew-normal/independent distribution, providing an appealing robust alternative to the routine use of symmetric normal distribution in this type of model. Specific distributions examined include univariate and multivariate versions of the skew-normal distribution, the skew-t distributions, the skew-slash distributions and the skew contaminated normal distributions. The methods developed is illustrated using a real data set from a dental clinical trial. (C) 2008 Elsevier B.V. All rights reserved.

Superoxide Dismutase 1-mediated Production of Ethanol- and DNA-derived Radicals in Yeasts Challenged with Hydrogen Peroxide MOLECULAR INSIGHTS INTO THE GENOME INSTABILITY OF PEROXIREDOXIN-NULL STRAINS

Peroxiredoxins are receiving increasing attention as defenders against oxidative damage and sensors of hydrogen peroxide-mediated signaling events. In the yeast Saccharomyces cerevisiae, deletion of one or more isoforms of the peroxiredoxins is not lethal but compromises genome stability by mechanisms that remain under scrutiny. Here, we show that cytosolic peroxiredoxin-null cells (tsa1 Delta tsa2 Delta) are more resistant to hydrogen peroxide than wildtype (WT) cells and consume it faster under fermentative conditions. Also, tsa1 Delta tsa2 Delta cells produced higher yields of the 1-hydroxyethyl radical from oxidation of the glucose metabolite ethanol, as proved by spin-trapping experiments. A major role for Fenton chemistry in radical formation was excluded by comparing WT and tsa1 Delta tsa2 Delta cells with respect to their levels of total and chelatable metal ions and of radical produced in the presence of chelators. The main route for 1-hydroxyethyl radical formation was ascribed to the peroxidase activity of Cu, Zn-superoxide dismutase (Sod1), whose expression and activity increased similar to 5- and 2-fold, respectively, in tsa1 Delta tsa2 Delta compared with WT cells. Accordingly, overexpression of human Sod1 in WT yeasts led to increased 1-hydroxyethyl radical production. Relevantly, tsa1 Delta tsa2 Delta cells challenged with hydrogen peroxide contained higher levels of DNA-derived radicals and adducts as monitored by immuno-spin trapping and incorporation of (14)C from glucose into DNA, respectively. The results indicate that part of hydrogen peroxide consumption by tsa1 Delta tsa2 Delta cells is mediated by induced Sod1, which oxidizes ethanol to the 1-hydroxyethyl radical, which, in turn, leads to increased DNA damage. Overall, our studies provide a pathway to account for the hypermutability of peroxiredoxin-null strains.

Saccharomyces cerevisiae coq10 null mutants are responsive to antimycin A

Deletion of COQ10 in Saccharomyces cerevisiae elicits a respiratory defect characterized by the absence of cytochrome c reduction, which is correctable by the addition of exogenous diffusible coenzyme Q(2). Unlike other coq mutants with hampered coenzyme Q(6) (Q(6)) synthesis, coq10 mutants have near wild-type concentrations of Q(6). In the present study, we used Q-cycle inhibitors of the coenzyme QH(2)-cytochrome c reductase complex to assess the electron transfer properties of coq10 cells. Our results show that coq10 mutants respond to antimycin A, indicating an active Q-cycle in these mutants, even though they are unable to transport electrons through cytochrome c and are not responsive to myxothiazol. EPR spectroscopic analysis also suggests that wild-type and coq10 mitochondria accumulate similar amounts of Q(6) semiquinone, despite a lower steady-state level of coenzyme QH(2)-cytochrome c reductase complex in the coq10 cells. Confirming the reduced respiratory chain state in coq10 cells, we found that the expression of the Aspergillus fumigatus alternative oxidase in these cells leads to a decrease in antimycin-dependent H(2)O(2) release and improves their respiratory growth.

Network genealogy of 195-bp satellite DNA supports the superimposed hybridization hypothesis of Trypanosoma cruzi evolutionary pattern

Trypanosoma cruzi is highly diverse genetically and has been partitioned into six discrete typing units (DTUs), recently re-named T. cruzi I-VI. Although T. cruzi reproduces predominantly by binary division, accumulating evidence indicates that particular DTUs are the result of hybridization events. Two major scenarios for the origin of the hybrid lineages have been proposed. It is accepted widely that the most heterozygous TcV and TcVI DTUs are the result of genetic exchange between TcII and TcIII strains. On the other hand, the participation of a TcI parental in the current genome structure of these hybrid strains is a matter of debate. Here, sequences of the T. cruzi-specific 195-bp satellite DNA of TcI, TcII, Tat, TcV, and TcVI strains have been used for inferring network genealogies. The resulting genealogy showed a high degree of reticulation, which is consistent with more than one event of hybridization between the Tc DTUs. The data also strongly suggest that Tat is a hybrid with two distinct sets of satellite sequences, and that genetic exchange between TcI and TcII parentals occurred within the pedigree of the TcV and TcVI DTUs. Although satellite DNAs belong to the fast-evolving portion of eukaryotic genomes, in >100 satellite units of nine T. cruzi strains we found regions that display 100% identity. No DTU-specific consensus motifs were identified, inferring species-wide conservation. (C) 2010 Elsevier B.V. All rights reserved.

Current account and capital mobility hypothesis: Evidence from the G-7

This paper investigates an intertemporal optimization model in order to analyze the current account of the G-7 countries, measured as the present value of the future changes in net output. The study compares observed and forecasted series, generated by the model, using Campbell & Shiller’s (1987) methodology. In the estimation process, the countries are considered separately (with OLS technique) as well as jointly (SURE approach), to capture contemporaneous correlations of the shocks in net output. The paper also proposes a note on Granger causality and its implications to the optimal current account. The empirical results are sensitive to the technique adopted in the estimation process and suggest a rejection of the model in the G-7 countries, except for the USA and Japan, according to some papers presented in the literature.