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.

Improved maximum likelihood estimators in a heteroskedastic errors-in-variables model

This paper develops a bias correction scheme for a multivariate heteroskedastic errors-in-variables model. The applicability of this model is justified in areas such as astrophysics, epidemiology and analytical chemistry, where the variables are subject to measurement errors and the variances vary with the observations. We conduct Monte Carlo simulations to investigate the performance of the corrected estimators. The numerical results show that the bias correction scheme yields nearly unbiased estimates. We also give an application to a real data set.

A multivariate ultrastructural errors-in-variables model with equation error

This paper deals with asymptotic results on a multivariate ultrastructural errors-in-variables regression model with equation errors Sufficient conditions for attaining consistent estimators for model parameters are presented Asymptotic distributions for the line regression estimators are derived Applications to the elliptical class of distributions with two error assumptions are presented The model generalizes previous results aimed at univariate scenarios (C) 2010 Elsevier Inc All rights reserved

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.

Improved maximum-likelihood estimation in a regression model with general parametrization

We analyse the finite-sample behaviour of two second-order bias-corrected alternatives to the maximum-likelihood estimator of the parameters in a multivariate normal regression model with general parametrization proposed by Patriota and Lemonte [A. G. Patriota and A. J. Lemonte, Bias correction in a multivariate regression model with genereal parameterization, Stat. Prob. Lett. 79 (2009), pp. 1655-1662]. The two finite-sample corrections we consider are the conventional second-order bias-corrected estimator and the bootstrap bias correction. We present the numerical results comparing the performance of these estimators. Our results reveal that analytical bias correction outperforms numerical bias corrections obtained from bootstrapping schemes.

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.

Robust inference in an heteroscedastic measurement error model

In this paper we deal with robust inference in heteroscedastic measurement error models Rather than the normal distribution we postulate a Student t distribution for the observed variables Maximum likelihood estimates are computed numerically Consistent estimation of the asymptotic covariance matrices of the maximum likelihood and generalized least squares estimators is also discussed Three test statistics are proposed for testing hypotheses of interest with the asymptotic chi-square distribution which guarantees correct asymptotic significance levels Results of simulations and an application to a real data set are also reported (C) 2009 The Korean Statistical Society Published by Elsevier B V All rights reserved

Exercise improves cardiovascular control in a model of dislipidemia and menopause

The present study investigated the effects of exercise training on arterial pressure, baroreflex sensitivity, cardiovascular autonomic control and metabolic parameters on female LDL-receptor knockout ovariectomized mice. Mice were divided into two groups: sedentary and trained. Trained group was submitted to an exercise training protocol. Blood cholesterol was measured. Arterial pressure (AP) signals were directly recorded in conscious mice. Baroreflex sensitivity was evaluated by tachycardic and bradycardic responses to AP changes. Cardiovascular autonomic modulation was measured in frequency (FFT) and time domains. Maximal exercise capacity was increased in trained as compared to sedentary group. Blood cholesterol was diminished in trained mice (191 +/- 8 mg/dL) when compared to sedentary mice (250 +/- 9 mg/dL, p<0.05). Mean AP and HR were reduced in trained group (101 +/- 3 mmHg and 535 +/- 14 bpm, p<0.05) when compared with sedentary group (125 +/- 3 mmHg and 600 +/- 12 bpm). Exercise training induced improvement in bradycardic reflex response in trained animals (-4.24 +/- 0.62 bpm/mmHg) in relation to sedentary animals (-1.49 +/- 0.15 bpm/mmHg, p<0.01); tachycardic reflex responses were similar between studied groups. Exercise training increased the variance (34 +/- 8 vs. 6.6 +/- 1.5 ms(2) in sedentary, p<0.005) and the high-frequency band (HF) of the pulse interval (IP) (53 +/- 7% vs. 26 +/- 6% in sedentary, p<0.01). It is tempting to speculate that results of this experimental study might represent a rationale for this non-pharmacological intervention in the management of cardiovascular risk factors in dyslipidemic post-menopause women. (C) 2009 Elsevier Ireland Ltd. All rights reserved.

Metabolic recovery of adipose tissue is associated with improvement in insulin resistance in a model of experimental diabetes

Obesity and insulin resistance are highly correlated with metabolic disturbances. Both the excess and lack of adipose tissue can lead to severe insulin resistance and diabetes. Adipose tissue plays an active role in energy homeostasis, hormone secretion, and other proteins that affect insulin sensitivity, appetite, energy balance, and lipid metabolism. Rats with streptozotocin-induced diabetes during the neonatal period develop the classic diabetic picture of hyperglycemia, hypoinsulinemia, and insulin resistance in adulthood. Low body weight and reduced epididymal (EP) fit mass were also seen in this model. The am) of this study was to investigate the glucose homeostasis and metabolic repercussions on the adipose tissue following chronic treatment with antidiabetic drugs in these animals. In the 4th week post birth, diabetic animals started an 8-week treatment with pioglitazone, metformin, or insulin.

Overweight and obesity related factors in schoolchildren in Santa Catarina State, Brazil

The purpose of this study is to determine the correlation of socioeconomic, dietary, and anthropometric-nutritional variables of parents and their children to overweight (including obesity) in schoolchildren in Santa Catarina State, Brazil. This is a transversal study conducted on 4,964, 6 to 10-year-old schoolchildren registered in 345 Santa Catarina elementary schools. The following data were acquired: the children`s current weight and height, birth weight and length, duration of breastfeeding, age at which water, herbal tea and other foods were introduced to their diet; parental income, education level, age, weight and height were also obtained. The prevalence of overweight and obese children were estimated by point and by interval with a 95% confidence; prevalence rates were obtained based on the Poisson model. An hierarchical approach was used, in which variables were adjusted within blocks and included in the model when they presented p<0.05 at the outcome (overweight including obesity). The results indicate that 47.8% of the subjects were male. The prevalence of overweight and obese students was 15.4% (C195%: 14.4%-16.5%) and 6.1% (CI95%: 5.4%-6.7%) respectively and were statistically similar among sexes and age ranges. BMI values were higher in males and among older children (p<0.05). After adjustment within and among blocks, the variables per capita household income and parents` BM I values remained associated with overweight (including obesity). Overweight (including obesity) in schoolchildren is associated with a higher per capita household income and parental overweight and obesity.

Correlation of the in vitro antifungal drug susceptibility with the in vivo activity of fluconazole in a murine model of cerebral infection caused by Cryptococcus gattii

Forty Cryptococcus gattii strains were submitted to antifungal susceptibility testing with fluconazole, itraconazole, amphotericin B and terbinafine. The minimum inhibitory concentration (MIC) ranges were 0.5-64.0 for fluconazole, < 0.015-0.25 for itraconazole, 0.015-0.5 for amphotericin B and 0.062-2.0 for terbinafine. A bioassay for the quantitation of fluconazole in murine brain tissue was developed. Swiss mice received daily injections of the antifungal, and their brains were withdrawn at different times over the 14-day study period. The drug concentrations varied from 12.98 to 44.60 mu g/mL. This assay was used to evaluate the therapy with fluconazole in a model of infection caused by C. gattii. Swiss mice were infected intracranially and treated with fluconazole for 7, 10 or 14 days. The treatment reduced the fungal burden, but an increase in fungal growth was observed on day 14. The MIC for fluconazole against sequential isolates was 16 mu g/mL, except for the isolates obtained from animals treated for 14 days (MIC = 64 mu g/mL). The quantitation of cytokines revealed a predominance of IFN-gamma and IL-12 in the non-treated group and elevation of IL-4 and IL-10 in the treated group. Our data revealed the possibility of acquired resistance during the antifungal drug therapy.

A Bayesian model for estimating the malaria transition probabilities considering individuals lost to follow-up

It is known that patients may cease participating in a longitudinal study and become lost to follow-up. The objective of this article is to present a Bayesian model to estimate the malaria transition probabilities considering individuals lost to follow-up. We consider a homogeneous population, and it is assumed that the considered period of time is small enough to avoid two or more transitions from one state of health to another. The proposed model is based on a Gibbs sampling algorithm that uses information of lost to follow-up at the end of the longitudinal study. To simulate the unknown number of individuals with positive and negative states of malaria at the end of the study and lost to follow-up, two latent variables were introduced in the model. We used a real data set and a simulated data to illustrate the application of the methodology. The proposed model showed a good fit to these data sets, and the algorithm did not show problems of convergence or lack of identifiability. We conclude that the proposed model is a good alternative to estimate probabilities of transitions from one state of health to the other in studies with low adherence to follow-up.

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].

Association between particulate matter from biomass burning and respiratory diseases in the southern region of the Brazilian Amazon

Objective. To investigate the short-term effects of exposure to particulate matter from biomass burning in the Amazon on the daily demand for outpatient care due to respiratory diseases in children and the elderly. Methods. Epidemiologic study with ecologic time series design. Daily consultation records were obtained from the 14 primary health care clinics in the municipality of Alta Floresta, state of Mato Grosso, in the southern region of the Brazilian Amazon, between January 2004 and December 2005. Information on the daily levels of fine particulate matter was made available by the Brazilian National Institute for Spatial Research. To control for confounding factors ( situations in which a non-causal association between exposure and disease is observed due to a third variable), variables related to time trends, seasonality, temperature, relative humidity, rainfall, and calendar effects ( such as occurrence of holidays and weekends) were included in the model. Poisson regression with generalized additive models was used. Results. A 10 mu g/m(3) increase in the level of exposure to particulate matter was associated with increases of 2.9% and 2.6% in outpatient consultations due to respiratory diseases in children on the 6th and 7th days following exposure. Significant associations were not observed for elderly individuals. Conclusions. The results suggest that the levels of particulate matter from biomass burning in the Amazon are associated with adverse effects on the respiratory health of children.

A model for the stabilization of atomic hydrogen centers in borate glasses

A previously proposed model describing the trapping site of the interstitial atomic hydrogen in borate glasses is analyzed. In this model the atomic hydrogen is stabilized at the centers of oxygen polygons belonging to B-O ring structures in the glass network by van der Waals forces. The previously reported atomic hydrogen isothermal decay experimental data are discussed in the light of this microscopic model. A coupled differential equation system of the observed decay kinetics was solved numerically using the Runge Kutta method. The experimental untrapping activation energy of 0.7 x 10(-19) J is in good agreement with the calculated results of dispersion interaction between the stabilized atomic hydrogen and the neighboring oxygen atoms at the vertices of hexagonal ring structures. (C) 2009 Elsevier B.V. All rights reserved.