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

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.

Influence diagnostics for linear models with first-order autoregressive elliptical errors

We introduce in this paper the class of linear models with first-order autoregressive elliptical errors. The score functions and the Fisher information matrices are derived for the parameters of interest and an iterative process is proposed for the parameter estimation. Some robustness aspects of the maximum likelihood estimates are discussed. The normal curvatures of local influence are also derived for some usual perturbation schemes whereas diagnostic graphics to assess the sensitivity of the maximum likelihood estimates are proposed. The methodology is applied to analyse the daily log excess return on the Microsoft whose empirical distributions appear to have AR(1) and heavy-tailed errors. (C) 2008 Elsevier B.V. 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.

Wavelet regression with correlated errors on a piecewise Holder class

This paper generalizes the methodology of Cat and Brown [Cai, T., Brown, L.D., 1998. Wavelet shrinkage for nonequispaced samples. The Annals of Statistics 26, 1783-1799] for wavelet shrinkage for nonequispaced samples, but in the presence of correlated stationary Gaussian errors. If the true function is a member of a piecewise Holder class, it is shown that, even for long memory errors, the rate of convergence of the procedure is almost-minimax relative to the independent and identically distributed errors case. (c) 2008 Elsevier B.V. All rights reserved.

A new class of survival regression models with heavy-tailed errors: robustness and diagnostics

Birnbaum-Saunders models have largely been applied in material fatigue studies and reliability analyses to relate the total time until failure with some type of cumulative damage. In many problems related to the medical field, such as chronic cardiac diseases and different types of cancer, a cumulative damage caused by several risk factors might cause some degradation that leads to a fatigue process. In these cases, BS models can be suitable for describing the propagation lifetime. However, since the cumulative damage is assumed to be normally distributed in the BS distribution, the parameter estimates from this model can be sensitive to outlying observations. In order to attenuate this influence, we present in this paper BS models, in which a Student-t distribution is assumed to explain the cumulative damage. In particular, we show that the maximum likelihood estimates of the Student-t log-BS models attribute smaller weights to outlying observations, which produce robust parameter estimates. Also, some inferential results are presented. In addition, based on local influence and deviance component and martingale-type residuals, a diagnostics analysis is derived. Finally, a motivating example from the medical field is analyzed using log-BS regression models. Since the parameter estimates appear to be very sensitive to outlying and influential observations, the Student-t log-BS regression model should attenuate such influences. The model checking methodologies developed in this paper are used to compare the fitted models.

Determination of sorbate and benzoate in beverage samples by capillary electrophoresis - Optimization of the method with inspection of ionic mobilities

The aim of this study was to develop a fast capillary electrophoresis method for the determination of benzoate and sorbate ions in commercial beverages. In the method development the pH and constituents of the background electrolyte were selected using the effective mobility versus pH curves. As the high resolution obtained experimentally for sorbate and benzoate in the studies presented in the literature is not in agreement with that expected from the ionic mobility values published, a procedure to determine these values was carried out. The salicylate ion was used as the internal standard. The background electrolyte was composed of 25 mmol L(-1) tris(hydroxymethyl)aminomethane and 12.5 mmol L(-1) 2-hydroxyisobutyric acid, atpH 8.1.Separation was conducted in a fused-silica capillary(32 cm total length and 8.5 cm effective length, 50 mu m I.D.), with short-end injection configuration and direct UV detection at 200 nm for benzoate and salicylate and 254 nm for sorbate ions. The run time was only 28 s. A few figures of merit of the proposed method include: good linearity (R(2) > 0.999), limit of detection of 0.9 and 0.3 mg L(-1) for benzoate and sorbate, respectively, inter-day precision better than 2.7% (n =9) and recovery in the range 97.9-105%. Beverage samples were prepared by simple dilution with deionized water (1:11, v/v). Concentrations in the range of 197-401 mg L(-1) for benzoate and 28-144 mg L(-1) for sorbate were found in soft drinks and tea. (c) 2008 Elsevier B.V. All rights reserved.

Communicative and psycholinguistic abilities in children with phenylketonuria and congenital hypothyroidism

The Neonatal Screening for Inborn Errors of Metabolism of the Association of Parents and Friends of Special Needs Individuals (APAE) - Bauru, Brazil, was implanted and accredited by the Brazilian Ministry of Health in 1998. It covers about 286 cities of the Bauru region and 420 collection spots. Their activities include screening, diagnosis, treatment and assistance to congenital hypothyroidism (CH) and phenylketonuria (PKU), among others. In 2005, a partnership was established with the Department of Speech-Language Pathology and Audiology, Bauru School of Dentistry, University of São Paulo, Bauru, seeking to characterize and to follow, by means of research studies, the development of the communicative abilities of children with CH and PKU. OBJECTIVE: The aim of this study was to describe communicative and psycholinguistic abilities in children with CH and PKU. MATERIALS AND METHODS: Sixty-eight children (25 children aged 1 to 120 months with PKU and 43 children aged 1 to 60 months with CH) participated in the study. The handbooks were analyzed and different instruments were applied (Observation of Communication Behavior, Early Language Milestone Scale, Peabody Picture Vocabulary Test, Gesell & Amatruda's Behavioral Development Scale, Portage Operation Inventory, Language Development Evaluation Scale, Denver Developmental Screening Test, ABFW Child Language Test-phonology and Illinois Test of Psycholinguistic Abilities), according to the children's age group and developmental level. RESULTS: It was observed that the children with PKU and CH at risk for alterations in their developmental abilities (motor, cognitive, linguistic, adaptive and personal-social), mainly in the first years of life. Alterations in the psycholinguistic abilities were also found, mainly after the preschool age. Attention deficits, language and cognitive alterations were more often observed in children with CH, while attention deficits with hyperactivity and alterations in the personal-social, language and motor adaptive abilities were more frequent in children with PKU. CONCLUSION: CH and PKU can cause communicative and psycholinguistic alterations that compromise the communication and affect the social integration and learning of these individuals, proving the need of having these abilities assisted by a speech and language pathologist.

Validity and reliability of methods for the detection of secondary caries around amalgam restorations in primary teeth

Secondary caries has been reported as the main reason for restoration replacement. The aim of this in vitro study was to evaluate the performance of different methods - visual inspection, laser fluorescence (DIAGNOdent), radiography and tactile examination - for secondary caries detection in primary molars restored with amalgam. Fifty-four primary molars were photographed and 73 suspect sites adjacent to amalgam restorations were selected. Two examiners evaluated independently these sites using all methods. Agreement between examiners was assessed by the Kappa test. To validate the methods, a caries-detector dye was used after restoration removal. The best cut-off points for the sample were found by a Receiver Operator Characteristic (ROC) analysis, and the area under the ROC curve (Az), and the sensitivity, specificity and accuracy of the methods were calculated for enamel (D2) and dentine (D3) thresholds. These parameters were found for each method and then compared by the McNemar test. The tactile examination and visual inspection presented the highest inter-examiner agreement for the D2 and D3 thresholds, respectively. The visual inspection also showed better performance than the other methods for both thresholds (Az = 0.861 and Az = 0.841, respectively). In conclusion, the visual inspection presented the best performance for detecting enamel and dentin secondary caries in primary teeth restored with amalgam.

Association between overbite and craniofacial growth pattern

The purpose of the present study was to assess the association between overbite and craniofacial growth pattern. The sample comprised eighty-six cephalograms obtained during the orthodontic pretreatment phase and analyzed using the Radiocef program to identify the craniofacial landmarks and perform orthodontic measurements. The variables utilized were overbite, the Jarabak percentage and the Vert index, as well as classifications resulting from the interpretation of these measurements. In all the statistical tests, a significance level of 5% was considered. Measurement reliability was checked by calculating method error. Weighted Kappa analysis showed that agreement between the facial types defined by the Vert index and the direction of growth trend established by the Jarabak percentage was not satisfactory. Owing to this lack of equivalency, a potential association between overbite and craniofacial growth pattern was evaluated using the chi-square test, considering the two methods separately. No relationship of dependence between overbite and craniofacial growth pattern was revealed by the results obtained. Therefore, it can be concluded that the classification of facial growth pattern will not be the same when considering the Jarabak and the Ricketts anayses, and that increased overbite cannot be associated with a braquifacial growth pattern, nor can openbite be associated with a dolichofacial growth pattern.

Propriedades mecânicas de peças com dimensões estruturais de Pinus spp: correlação entre resistência à tração e classificação visual

A redução da disponibilidade de espécies de madeiras nativas e seus efeitos na economia, associada ao fortalecimento dos conceitos de preservação ambiental, criou a necessidade de desenvolvimento de alternativas viáveis para utilização racional de espécies de reflorestamento. E uma das opções é a realização de classificação visual das peças. Autores de trabalhos desenvolvidos nessa linha de pesquisa verificaram a adequação das regras de classificação visual do Southern Pine Inspection Bureau (SPIB) dos EUA à madeira de Pinus do Brasil e apresentaram proposta para normalizar o processo de classificação visual dessa madeira. Nessa classificação, os aspectos com maior influência são: presença de nós, desvio de grã em relação ao eixo da peça e densidade de anéis de crescimento. Assim, esta pesquisa apresenta um estudo experimental que consistiu na classificação visual e determinação da resistência à tração de 85 peças de Pinus spp e um estudo teórico, que propôs uma equação para determinar a resistência à tração média de peças estruturais em função da classificação visual. Com este trabalho, foi possível observar a influência dos nós e dos anéis de crescimento sobre a resistência à tração das peças analisadas.

Sob o signo de Darwin? Sobre o mau uso de uma quimera

No ano de 2003 Francisco de Oliveria publicou um artigo intitulado "O Ornitorrinco" no qual fez considerações críticas sobre a conjectura politico-social daquele momento histórico. Tal artigo é permeado por um paralelo entre o evolucionismo darwinista e a visão do autor sobre a sociedade brasileira contemporânea. Entretanto, ao fazer tal analogia ele incorre numa série de equívocos teóricos sobre a teoria evolucionista. Tais equívocos consistem, em grande parte, numa substuição indevida entre aquilo que ficou conhecido como Darwinismo Social e a teoria neodarwinista como entendida pelos seus atuais proponentes. O presente trabalho identifica estes equívocos e os contextualiza dentro da teoria neodarwiniana. Além disso, fazemos um recorte histórico do processo de formação do pensamento evolucionista para enfatizar que a associação entre biologia e darwinismo social é mais complexa do que geralmente se assume.

Does hepatocellular carcinoma in non-alcoholic steatohepatitis exist in cirrhotic and non-cirrhotic patients?

Non-alcoholic steatohepatitis (NASH) has been associated with hepatocellular carcinoma (HCC) often arising in histologically advanced disease when steatohepatitis is not active (cryptogenic cirrhosis). Our objective was to characterize patients with HCC and active, histologically defined steatohepatitis. Among 394 patients with HCC detected by ultrasound imaging over 8 years and staged by the Barcelona Clinic Liver Cancer (BCLC) criteria, we identified 7 cases (1.7%) with HCC occurring in the setting of active biopsy-proven NASH. All were negative for other liver diseases such as hepatitis C, hepatitis B, autoimmune hepatitis, Wilson disease, and hemochromatosis. The patients (4 males and 3 females, age 63 ± 13 years) were either overweight (4) or obese (3); 57% were diabetic and 28.5% had dyslipidemia. Cirrhosis was present in 6 of 7 patients, but 1 patient had well-differentiated HCC in the setting of NASH without cirrhosis (fibrosis stage 1) based on repeated liver biopsies, the absence of portal hypertension by clinical and radiographic evaluations and by direct surgical inspection. Among the cirrhotic patients, 71.4% were clinically staged as Child A and 14.2% as Child B. Tumor size ranged from 1.0 to 5.2 cm and 5 of 7 patients were classified as early stage; 46% of all nodules were hyper-echoic and 57% were <3 cm. HCC was well differentiated in 1/6 and moderately differentiated in 5/6. Alpha-fetoprotein was <100 ng/mL in all patients. HCC in patients with active steatohepatitis is often multifocal, may precede clinically advanced disease and occurs without diagnostic levels of alpha-fetoprotein. Importantly, HCC may occur in NASH in the absence of cirrhosis. More aggressive screening of NASH patients may be warranted.

Pre-processing for noise detection in gene expression classification data

Due to the imprecise nature of biological experiments, biological data is often characterized by the presence of redundant and noisy data. This may be due to errors that occurred during data collection, such as contaminations in laboratorial samples. It is the case of gene expression data, where the equipments and tools currently used frequently produce noisy biological data. Machine Learning algorithms have been successfully used in gene expression data analysis. Although many Machine Learning algorithms can deal with noise, detecting and removing noisy instances from the training data set can help the induction of the target hypothesis. This paper evaluates the use of distance-based pre-processing techniques for noise detection in gene expression data classification problems. This evaluation analyzes the effectiveness of the techniques investigated in removing noisy data, measured by the accuracy obtained by different Machine Learning classifiers over the pre-processed data.