Estimation and diagnostics for heteroscedastic nonlinear regression models based on scale mixtures of skew-normal distributions

An extension of some standard likelihood based procedures to heteroscedastic nonlinear regression models under scale mixtures of skew-normal (SMSN) distributions is developed. This novel class of models provides a useful generalization of the heteroscedastic symmetrical nonlinear regression models (Cysneiros et al., 2010), since the random term distributions cover both symmetric as well as asymmetric and heavy-tailed distributions such as skew-t, skew-slash, skew-contaminated normal, among others. A simple EM-type algorithm for iteratively computing maximum likelihood estimates of the parameters is presented and the observed information matrix is derived analytically. In order to examine the performance of the proposed methods, some simulation studies are presented to show the robust aspect of this flexible class against outlying and influential observations and that the maximum likelihood estimates based on the EM-type algorithm do provide good asymptotic properties. Furthermore, local influence measures and the one-step approximations of the estimates in the case-deletion model are obtained. Finally, an illustration of the methodology is given considering a data set previously analyzed under the homoscedastic skew-t nonlinear regression model. (C) 2012 Elsevier B.V. All rights reserved.

Electric Ventilation: indications for and technical aspects of diaphragm pacing stimulation surgical implantation

Objective: Patients with high cervical spinal cord injury are usually dependent on mechanical ventilation support, which, albeit life saving, is associated with complications and decreased life expectancy because of respiratory infections. Diaphragm pacing stimulation (DPS), sometimes referred to as electric ventilation, induces inhalation by stimulating the inspiratory muscles. Our objective was to highlight the indications for and some aspects of the surgical technique employed in the laparoscopic insertion of the DPS electrodes, as well as to describe five cases of tetraplegic patients submitted to the technique. Methods: Patient selection involved transcutaneous phrenic nerve studies in order to determine whether the phrenic nerves were preserved. The surgical approach was traditional laparoscopy, with four ports. The initial step was electrical mapping in order to locate the "motor points" (the points at which stimulation would cause maximal contraction of the diaphragm). If the diaphragm mapping was successful, four electrodes were implanted into the abdominal surface of the diaphragm, two on each side, to stimulate the branches of the phrenic nerve. Results: Of the five patients, three could breathe using DPS alone for more than 24 h, one could do so for more than 6 h, and one could not do so at all. Conclusions: Although a longer follow-up period is needed in order to reach definitive conclusions, the initial results have been promising. At this writing, most of our patients have been able to remain ventilator-free for long periods of time.

Influence diagnostics in heteroscedastic and/or autoregressive nonlinear elliptical models for correlated data

In this paper, we propose nonlinear elliptical models for correlated data with heteroscedastic and/or autoregressive structures. Our aim is to extend the models proposed by Russo et al. [22] by considering a more sophisticated scale structure to deal with variations in data dispersion and/or a possible autocorrelation among measurements taken throughout the same experimental unit. Moreover, to avoid the possible influence of outlying observations or to take into account the non-normal symmetric tails of the data, we assume elliptical contours for the joint distribution of random effects and errors, which allows us to attribute different weights to the observations. We propose an iterative algorithm to obtain the maximum-likelihood estimates for the parameters and derive the local influence curvatures for some specific perturbation schemes. The motivation for this work comes from a pharmacokinetic indomethacin data set, which was analysed previously by Bocheng and Xuping [1] under normality.

Influence diagnostics in Gaussian spatial linear models

Spatial linear models have been applied in numerous fields such as agriculture, geoscience and environmental sciences, among many others. Spatial dependence structure modelling, using a geostatistical approach, is an indispensable tool to estimate the parameters that define this structure. However, this estimation may be greatly affected by the presence of atypical observations in the sampled data. The purpose of this paper is to use diagnostic techniques to assess the sensitivity of the maximum-likelihood estimators, covariance functions and linear predictor to small perturbations in the data and/or the spatial linear model assumptions. The methodology is illustrated with two real data sets. The results allowed us to conclude that the presence of atypical values in the sample data have a strong influence on thematic maps, changing the spatial dependence structure.

Comparison of fast-track diagnostics respiratory pathogens multiplex real-time RT-PCR assay with in-house singleplex assays for comprehensive detection of human respiratory viruses

Fast-track Diagnostics respiratory pathogens (FTDRP) multiplex real-time RT-PCR assay was compared with in-house singleplex real-time RT-PCR assays for detection of 16 common respiratory viruses. The FTDRP assay correctly identified 26 diverse respiratory virus strains, 35 of 41 (85%) external quality assessment samples spiked with cultured virus and 232 of 263 (88%) archived respiratory specimens that tested positive for respiratory viruses by in-house assays. Of 308 prospectively tested respiratory specimens selected from children hospitalized with acute respiratory illness, 270 (87.7%) and 265 (86%) were positive by FTDRP and in-house assays for one or more viruses, respectively, with combined test results showing good concordance (K=0.812, 95% CI = 0.786-0.838). Individual FTDRP assays for adenovirus, respiratory syncytial virus and rhinovirus showed the lowest comparative sensitivities with in-house assays, with most discrepancies occurring with specimens containing low virus loads and failed to detect some rhinovirus strains, even when abundant. The FTDRP enterovirus and human bocavirus assays appeared to be more sensitive than the in-house assays with some specimens. With the exceptions noted above, most FTDRP assays performed comparably with in-house assays for most viruses while offering enhanced throughput and easy integration by laboratories using conventional real-time PCR instrumentation. Published by Elsevier B.V.

Influence diagnostics for elliptical semiparametric mixed models

In this paper we extend semiparametric mixed linear models with normal errors to elliptical errors in order to permit distributions with heavier and lighter tails than the normal ones. Penalized likelihood equations are applied to derive the maximum penalized likelihood estimates (MPLEs) which appear to be robust against outlying observations in the sense of the Mahalanobis distance. A reweighed iterative process based on the back-fitting method is proposed for the parameter estimation and the local influence curvatures are derived under some usual perturbation schemes to study the sensitivity of the MPLEs. Two motivating examples preliminarily analyzed under normal errors are reanalyzed considering some appropriate elliptical errors. The local influence approach is used to compare the sensitivity of the model estimates.

Head & neck optical diagnostics: vision of the future of surgery

Review paper and Proceedings of the Inaugural Meeting of the Head and Neck Optical Diagnostics Society (HNODS) on March 14th 2009 at University College London.

The future of medical diagnostics: review paper

While histopathology of excised tissue remains the gold standard for diagnosis, several new, non-invasive diagnostic techniques are being developed. They rely on physical and biochemical changes that precede and mirror malignant change within tissue. The basic principle involves simple optical techniques of tissue interrogation. Their accuracy, expressed as sensitivity and specificity, are reported in a number of studies suggests that they have a potential for cost effective, real-time, in situ diagnosis.

Water transfer from São Francisco river to semiarid northeast of Brazil: technical data, environmental impacts, survey of opinion about the amount to be transferred

The transposition of the São Francisco River is considered one of the greatest engineering works in Brazil of all time since it will cross an extensive agricultural region of continental dimensions, involving environmental impacts, water, soil, irrigation, water payment and other multidisciplinary themes. Taking into account its importance, this subject was incorporated into a discipline of UFSCar (Federal University of São Carlos - Brazil) named "Pollution and Environmental Impacts". It was noted strong reaction against the project, even before the presentation. To allow a critical analysis, the first objective was to compile the main technical data and environmental impacts. The second objective was to detect the three most important aspects that cause reaction, concluding for the following reasons: assumption that the volume of water to be transferred was much greater than it actually is proposed in the project; lack of knowledge about similar project already done in Brazil; the idea that the artificial canal to be built was much broader than that proposed by the project. The participants' opinion about "volume to be transferred" was raised quantitatively four times: 2-undergraduate students; 1-graduate; 1-outside community. The average resulted 14 times larger than that proposed in the project, significant according to t-test. It was concluded that the reaction to water transfer project is due in part to the ignorance combined with a preconceived idea that tend to overestimate the magnitude of environmental impacts.