On estimation and influence diagnostics for log-Birnbaum-Saunders Student-t regression models: Full Bayesian analysis

The purpose of this paper is to develop a Bayesian approach for log-Birnbaum-Saunders Student-t regression models under right-censored survival data. Markov chain Monte Carlo (MCMC) methods are used to develop a Bayesian procedure for the considered model. In order to attenuate the influence of the outlying observations on the parameter estimates, we present in this paper Birnbaum-Saunders models in which a Student-t distribution is assumed to explain the cumulative damage. Also, some discussions on the model selection to compare the fitted models are given and case deletion influence diagnostics are developed for the joint posterior distribution based on the Kullback-Leibler divergence. The developed procedures are illustrated with a real data set. (C) 2010 Elsevier B.V. All rights reserved.

Statistical analysis of proficiency testing results under elliptical distributions

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.

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].

STABILITY ANALYSIS WITH APPLICATIONS OF A TWO-DIMENSIONAL DYNAMICAL SYSTEM ARISING FROM A STOCHASTIC MODEL FOR AN ASSET MARKET

We analyze the stability properties of equilibrium solutions and periodicity of orbits in a two-dimensional dynamical system whose orbits mimic the evolution of the price of an asset and the excess demand for that asset. The construction of the system is grounded upon a heterogeneous interacting agent model for a single risky asset market. An advantage of this construction procedure is that the resulting dynamical system becomes a macroscopic market model which mirrors the market quantities and qualities that would typically be taken into account solely at the microscopic level of modeling. The system`s parameters correspond to: (a) the proportion of speculators in a market; (b) the traders` speculative trend; (c) the degree of heterogeneity of idiosyncratic evaluations of the market agents with respect to the asset`s fundamental value; and (d) the strength of the feedback of the population excess demand on the asset price update increment. This correspondence allows us to employ our results in order to infer plausible causes for the emergence of price and demand fluctuations in a real asset market. The employment of dynamical systems for studying evolution of stochastic models of socio-economic phenomena is quite usual in the area of heterogeneous interacting agent models. However, in the vast majority of the cases present in the literature, these dynamical systems are one-dimensional. Our work is among the few in the area that construct and study analytically a two-dimensional dynamical system and apply it for explanation of socio-economic phenomena.

Leverage analysis for linear mixed models

We consider a generalized leverage matrix useful for the identification of influential units and observations in linear mixed models and show how a decomposition of this matrix may be employed to identify high leverage points for both the marginal fitted values and the random effect component of the conditional fitted values. We illustrate the different uses of the two components of the decomposition with a simulated example as well as with a real data set.

Missing data mechanisms and their implications on the analysis of categorical data

We review some issues related to the implications of different missing data mechanisms on statistical inference for contingency tables and consider simulation studies to compare the results obtained under such models to those where the units with missing data are disregarded. We confirm that although, in general, analyses under the correct missing at random and missing completely at random models are more efficient even for small sample sizes, there are exceptions where they may not improve the results obtained by ignoring the partially classified data. We show that under the missing not at random (MNAR) model, estimates on the boundary of the parameter space as well as lack of identifiability of the parameters of saturated models may be associated with undesirable asymptotic properties of maximum likelihood estimators and likelihood ratio tests; even in standard cases the bias of the estimators may be low only for very large samples. We also show that the probability of a boundary solution obtained under the correct MNAR model may be large even for large samples and that, consequently, we may not always conclude that a MNAR model is misspecified because the estimate is on the boundary of the parameter space.

Bayesian Analysis for Nonlinear Regression Model Under Skewed Errors, with Application in Growth Curves

We have considered a Bayesian approach for the nonlinear regression model by replacing the normal distribution on the error term by some skewed distributions, which account for both skewness and heavy tails or skewness alone. The type of data considered in this paper concerns repeated measurements taken in time on a set of individuals. Such multiple observations on the same individual generally produce serially correlated outcomes. Thus, additionally, our model does allow for a correlation between observations made from the same individual. We have illustrated the procedure using a data set to study the growth curves of a clinic measurement of a group of pregnant women from an obstetrics clinic in Santiago, Chile. Parameter estimation and prediction were carried out using appropriate posterior simulation schemes based in Markov Chain Monte Carlo methods. Besides the deviance information criterion (DIC) and the conditional predictive ordinate (CPO), we suggest the use of proper scoring rules based on the posterior predictive distribution for comparing models. For our data set, all these criteria chose the skew-t model as the best model for the errors. These DIC and CPO criteria are also validated, for the model proposed here, through a simulation study. As a conclusion of this study, the DIC criterion is not trustful for this kind of complex model.

Regression analysis of mean quality-adjusted survival time based on pseudo-observations

Regression models for the mean quality-adjusted survival time are specified from hazard functions of transitions between two states and the mean quality-adjusted survival time may be a complex function of covariates. We discuss a regression model for the mean quality-adjusted survival (QAS) time based on pseudo-observations, which has the advantage of directly modeling the effect of covariates in the QAS time. Both Monte Carlo Simulations and a real data set are studied. Copyright (C) 2009 John Wiley & Sons, Ltd.

Local Influence Analysis for Skew-Normal Linear Mixed Models

In this article, we consider local influence analysis for the skew-normal linear mixed model (SN-LMM). As the observed data log-likelihood associated with the SN-LMM is intractable, Cook`s well-known approach cannot be applied to obtain measures of local influence. Instead, we develop local influence measures following the approach of Zhu and Lee (2001). This approach is based on the use of an EM-type algorithm and is measurement invariant under reparametrizations. Four specific perturbation schemes are discussed. Results obtained for a simulated data set and a real data set are reported, illustrating the usefulness of the proposed methodology.

Bayesian Analysis for the Generalized Lognormal Distribution Applied to Failure Time Analysis

There are several versions of the lognormal distribution in the statistical literature, one is based in the exponential transformation of generalized normal distribution (GN). This paper presents the Bayesian analysis for the generalized lognormal distribution (logGN) considering independent non-informative Jeffreys distributions for the parameters as well as the procedure for implementing the Gibbs sampler to obtain the posterior distributions of parameters. The results are used to analyze failure time models with right-censored and uncensored data. The proposed method is illustrated using actual failure time data of computers.

Oral health conditions among the elderly in Southeastern São Paulo State

OBJECTIVE: This study aimed to asses oral health conditions in a population aged 60 years and over living in Botucatu, Southeastern Brazil. A cross-sectional population-based study was carried out using a random sample (N=372) of the urban population aged 60 years and over from the city of Botucatu, in 2005. World Health Organization criteria and codes for oral health epidemiological surveys were used. Re-examination was carried out in 10% of individuals aiming to evaluate intra-examiner agreement. Statistical analysis was performed by one-way ANOVA or Kruskal-Wallis ANOVA, as applicable. Also, the t-test was used in the absence of homoscedasticity. Fisher's exact test was used for situations where the categories with less than five units were observed. Adjusted residuals and multiple-comparison analysis were conducted to identify associations between variable categories and subgroups. The intra-examiner agreement was 98% and Kappa statistics result was 0.95. Loss component represented 90.68% of DMF-T index, which was 29.85. The prevalence of edentulism was 63.17%. Upper and lower dentures were found in 80% and 58% respectively, with complete denture as the most commonly used. In those studied, 15% required upper and 38% lower dentures. There was more need for complete denture in both jaws. Approximately 20% had soft tissue alterations. For periodontal conditions, most sextants were excluded (81.81%). Periodontal pockets (4 - 5 mm) were seen in 11.29% of the examined individuals. The oral health status of the elderly population in Botucatu is poor, as well as in other Brazilian cities. The results of this study may help planning collective health actions, giving an accurate description of the oral problems among the elderly.

Digital subtraction radiographic analysis of the combination of bioabsorbable membrane and bovine morphogenetic protein pool in human periodontal infrabony defects

OBJECTIVES: This study assessed the bone density gain and its relationship with the periodontal clinical parameters in a case series of a regenerative therapy procedure. MATERIAL AND METHODS: Using a split-mouth study design, 10 pairs of infrabony defects from 15 patients were treated with a pool of bovine bone morphogenetic proteins associated with collagen membrane (test sites) or collagen membrane only (control sites). The periodontal healing was clinically and radiographically monitored for six months. Standardized pre-surgical and 6-month postoperative radiographs were digitized for digital subtraction analysis, which showed relative bone density gain in both groups of 0.034 ± 0.423 and 0.105 ± 0.423 in the test and control group, respectively (p>0.05). RESULTS: As regards the area size of bone density change, the influence of the therapy was detected in 2.5 mm² in the test group and 2 mm² in the control group (p>0.05). Additionally, no correlation was observed between the favorable clinical results and the bone density gain measured by digital subtraction radiography (p>0.05). CONCLUSIONS: The findings of this study suggest that the clinical benefit of the regenerative therapy observed did not come with significant bone density gains. Long-term evaluation may lead to a different conclusions.

Isolation of Pseudomonas aeruginosa strains from dental office environments and units in Barretos, state of São Paulo, Brazil, and analysis of their susceptibility to antimicrobial drugs

A wide variety of opportunistic pathogens has been detected in the tubing supplying water to odontological equipment, in special in the biofilm lining of these tubes. Among these pathogens, Pseudomonas aeruginosa, one of the leading causes of nosocomial infections, is frequently found in water lines supplying dental units. In the present work, 160 samples of water, and 200 fomite samples from forty dental units were collected in the city of Barretos, State of São Paulo, Brazil and evaluated between January and July, 2005. Seventy-six P. aeruginosa strains, isolated from the dental environment (5 strains) and water system (71 strains), were tested for susceptibility to six antimicrobial drugs most frequently used against P. aeruginosa infections. Susceptibility to ciprofloxacin, followed by meropenem was the predominant profile. The need for effective means of reducing the microbial burden within dental unit water lines is emphasized, and the risk of exposure and cross-infection in dental practice, in special when caused by opportunistic pathogens like P. aeruginosa, are highlighted.

Analysis of TMJ vibration sounds before and after use of two types of occlusal splints

Temporomandibular joint (TMJ) sounds are important and common physical signs of temporomandibular disorders (TMD). The aim of this study was to evaluate the influence of the effect of the use of occlusal bite splints (stabilizing and repositioning) on the sounds produced in the TMJ, by means of the electrovibratography (EVG). Thirty-one patients with TMD from the Dental School of Ribeirão Preto, University of São Paulo, Brazil were selected for this study. Group 1 (n=23) wore stabilizing bite splints and Group 2 (n=8) used anterior repositioning splints. Before and after treatment with occlusal splints both groups were analyzed using the SonoPAK Q/S recording system (BioResearch System, Inc.). The treatments with stabilizing bite splints were satisfactory, since they reduced the total amount of the sound energies (p<0.05), but the use of anterior repositioning splints for no more than 4 weeks produced significantly better results (p<0.01). The total amount of vibration energy involved in the vibrating movements of the TMJ showed significant improvement using anterior repositioning splints.

Adhesion of an endodontic sealer to dentin and gutta-percha: shear and push-out bond strength measurements and SEM analysis

The use of an adequate method for evaluation of the adhesion of root canal filling materials provides more reliable results to allow comparison of the materials and substantiate their clinical choice. The aims of this study were to compare the shear bond strength (SBS) test and push-out test for evaluation of the adhesion of an epoxy-based endodontic sealer (AH Plus) to dentin and gutta-percha, and to assess the failure modes on the debonded surfaces by means of scanning electron microscopy (SEM). Three groups were established (n=7): in group 1, root cylinders obtained from human canines were embedded in acrylic resin and had their canals prepared and filled with sealer; in group 2, longitudinal sections of dentin cylinders were embedded in resin with the canal surface smoothed and turned upwards; in group 3, gutta-percha cylinders were embedded in resin. Polyethylene tubes filled with sealer were positioned on the polished surface of the specimens (groups 2 and 3). The push-out test (group 1) and the SBS test (groups 2 and 3) were performed in an Instron universal testing machine running at crosshead speed of 1 mm/min. Means (±SD) in MPa were: G1 (8.8±1.13), G2 (5.9±1.05) and G3 (3.8±0.55). Statistical analysis by ANOVA and Student's t-test (a=0.05) revealed statistically significant differences (p<0.01) among the groups. SEM analysis showed a predominance of adhesive and mixed failures of AH Plus sealer. The tested surface affected significantly the results with the sealer reaching higher bond strength to dentin than to gutta-percha with the SBS test. The comparison of the employed methodologies showed that the SBS test produced significantly lower bond strength values than the push-out test, was skilful in determining the adhesion of AH Plus sealer to dentin and gutta-percha, and required specimens that could be easily prepared for SEM, presenting as a viable alternative for further experiments.