Assessing relationships between genetic evaluations using robust regression with an application to holsteins in Uruguay

Globalization of dairy cattle breeding has created a need for international sire proofs. Some early methods for converting proofs from one population to another are based on simple linear regression. An alternative robust regression method based on the t-distribution is presented, and maximum likelihood and Bayesian techniques for analysis are described, including the situation in which some proofs are missing. Procedures were used to investigate the relationship between Holstein sire proofs obtained by two Uruguayan genetic evaluation programs. The results suggest that conversion equations developed from data including only sires having proofs in both populations can lead to distorted results, relative to estimates obtained using techniques for incomplete data. There was evidence of non-normality of regression residuals, which constitutes an additional source of bias. A robust estimator may not solve all problems, but can provide simple conversion equations that are less sensitive to outlying proofs and to departures from assumptions.

Detecção de outliers espaciais: refinamento de similaridade e desempenho

Pós-graduação em Ciência da Computação - IBILCE

A comparative analysis of caries and fluorosis among cities with and without public water supply fluoridation in São Paulo State, Brazil

Purpose: This population-based, cross-sectional study aimed to record the DMFT index for 12 year-old children with dental caries and fluorosis levels in cities with and without public water supply fluoridation. Methods: From the 101 municipalities belonging to the Health Regional Department XV (DRSXV-SJRP) of the São Paulo state in the Southeast region of Brazil, 85 cities were selected after exclusion of those with incomplete data and less than ten years of fluoridation treatment in 2004. The criteria adopted for the assessment of dental caries and fluorosis levels were based on the guidelines published in the WHO Manual 4th edition. The data were analyzed using Fisher’s exact tests at a significance level of 5%. Results: The prevalence of caries in 12 year-old children had no significant association with fluoridated water, and was considered “moderate” and “high” in cities without fluoridation and “low” and “moderate” in cities with fluoridation. A significant association was found between water fluoridation and fluorosis (P=0.001), but not between water fluoridation and the DMFT index (P=0.119). Conclusion: The prevalence of fluorosis was related to water fluoridation in this study. However, fluorosis was also observed in non-fluoridated cities, which may result from fluoride intake through other sources.

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.

Influence Assessment in an Heteroscedastic Errors-in-Variables Model

The main goal of this article is to consider influence assessment in models with error-prone observations and variances of the measurement errors changing across observations. The techniques enable to identify potential influential elements and also to quantify the effects of perturbations in these elements on some results of interest. The approach is illustrated with data from the WHO MONICA Project on cardiovascular disease.

Robust statistical modeling using the Birnbaum-Saunders-t distribution applied to insurance

In this paper, we carry out robust modeling and influence diagnostics in Birnbaum-Saunders (BS) regression models. Specifically, we present some aspects related to BS and log-BS distributions and their generalizations from the Student-t distribution, and develop BS-t regression models, including maximum likelihood estimation based on the EM algorithm and diagnostic tools. In addition, we apply the obtained results to real data from insurance, which shows the uses of the proposed model. Copyright (c) 2011 John Wiley & Sons, Ltd.

Global Change and the World's Mountains-Research Needs and Emerging Themes for Sustainable Development A Synthesis From the 2010 Perth II Conference

The conference on Global Change and the World’s Mountains held in Perth, Scotland, in 2010 offered a unique opportunity to analyze the state and progress of mountain research and its contribution to sustainable mountain development, as well as to reflect on required reorientations of research agendas. In this paper we provide the results of a three-step assessment of the research presented by 450 researchers from around the world. First, we determined the state of the art of mountain research and categorized it based on the analytical structure of the Global Land Project (GLP 2005). Second, we identified emerging themes for future research. Finally, we assessed the contribution of mountain research to sustainable development along the lines of the Grand Challenges in Global Sustainability Research (International Council for Science 2010). Analysis revealed that despite the growing recognition of the importance of more integrative research (inter- and transdisciplinary), the research community gathered in Perth still focuses on environmental drivers of change and on interactions within ecological systems. Only a small percentage of current research seeks to enhance understanding of social systems and of interactions between social and ecological systems. From the ecological systems perspective, a greater effort is needed to disentangle and assess different drivers of change and to investigate impacts on the rendering of ecosystem services. From the social systems perspective, significant shortcomings remain in understanding the characteristics, trends, and impacts of human movements to, within, and out of mountain areas as a form of global change. Likewise, sociocultural drivers affecting collective behavior as well as incentive systems devised by policy and decision makers are little understood and require more in-depth investigation. Both the complexity of coupled social– ecological systems and incomplete data sets hinder integrated systems research. Increased understanding of linkages and feedbacks between social and ecological systems will help to identify nonlinearities and thresholds (tipping points) in both system types. This presupposes effective collaboration between ecological and social sciences. Reflections on the Grand Challenges in Sustainability Research put forth by the International Council for Science (2010) reveal the need to intensify research on effective responses and innovations. This will help to achieve sustainable development in mountain regions while maintaining the core competence of mountain research in forecasting and observation.

Golden-winged Warbler habitat model validation for northern Wisconsin and central Minnesota

Between 1966 and 2003, the Golden-winged Warbler (Vermivora chrysoptera) experienced declines of 3.4% per year in large parts of the breeding range and has been identified by Partners in Flight as one of 28 land birds requiring expedient action to prevent its continued decline. It is currently being considered for listing under the Endangered Species Act. A major step in advancing our understanding of the status and habitat preferences of Golden-winged Warbler populations in the Upper Midwest was initiated by the publication of new predictive spatially explicit Golden-winged Warbler habitat models for the northern Midwest. Here, I use original data on observed Golden-winged Warbler abundances in Wisconsin and Minnesota to compare two population models: the hierarchical spatial count (HSC) model with the Habitat Suitability Index (HSI) model. I assessed how well the field data compared to the model predictions and found that within Wisconsin, the HSC model performed slightly better than the HSI model whereas both models performed relatively equally in Minnesota. For the HSC model, I found a 10% error of commission in Wisconsin and a 24.2% error of commission for Minnesota. Similarly, the HSI model has a 23% error of commission in Minnesota; in Wisconsin due to limited areas where the HSI model predicted absences, there was incomplete data and I was unable to determine the error of commission for the HSI model. These are sites where the model predicted presences and the Golden-winged Warbler did not occur. To compare predicted abundance from the two models, a 3x3 contingency table was used. I found that when overlapped, the models do not complement one another in identifying Golden-winged Warbler presences. To calculate discrepancy between the models, the error of commission shows that the HSI model has only a 6.8% chance of correctly classifying absences in the HSC model. The HSC model has only 3.3% chance of correctly classifying absences in the HSI model. These findings highlight the importance of grasses for nesting, shrubs used for cover and foraging, and trees for song perches and foraging as key habitat characteristics for breeding territory occupancy by singing males.

Minimally invasive surgery when treating endometriosis has a positive effect on health and on quality of work life of affected women

STUDY QUESTION: What is the effect of the minimally invasive surgical treatment of endometriosis on health and on quality of work life (e.g. working performance) of affected women? SUMMARY ANSWER: Absence from work, performance loss and the general negative impact of endometriosis on the job are reduced significantly by the laparoscopic surgery. WHAT IS KNOWN ALREADY: The benefits of surgery overall and of the laparoscopic method in particular for treating endometriosis have been described before. However, previous studies focus on medical benchmarks without including the patient's perspective in a quantitative manner. STUDY DESIGN, SIZE, DURATION: A retrospective questionnaire-based survey covering 211 women with endometriosis and a history of specific laparoscopic surgery in a Swiss university hospital, tertiary care center. Data were returned anonymously and were collected from the beginning of 2012 until March 2013. PARTICIPANTS/MATERIALS, SETTING, METHODS: Women diagnosed with endometriosis and with at least one specific laparoscopic surgery in the past were enrolled in the study. The study investigated the effect of the minimally invasive surgery on health and on quality of work life of affected women. Questions used were obtained from the World Endometriosis Research Foundation (WERF) Global Study on Women's Health (GSWH) instrument. The questionnaire was shortened and adapted for the purpose of the present study. MAIN RESULTS AND THE ROLE OF CHANCE: Of the 587 women invited to participate in the study, 232 (232/587 = 40%) returned the questionnaires. Twenty-one questionnaires were excluded due to incomplete data and 211 sets (211/587 = 36%) were included in the study. Our data show that 62% (n = 130) of the study population declared endometriosis as influencing the job during the period prior to surgery, compared with 28% after surgery (P < 0.001). The mean (maximal) absence from work due to endometriosis was reduced from 2.0 (4.9) to 0.5 (1.4) hours per week (P < 0.001). The mean (maximal) loss in working performance after the surgery averaged out at 5.7% (12.6%) compared with 17.5% (30.5%) before this treatment (P < 0.001). LIMITATIONS, REASONS FOR CAUTION: The mediocre response rate of the study weakens the representativeness of the investigated population. Considering the anonymous setting a non-responder investigation was not performed. A bias due to selection, information and negativity effects within a retrospective survey cannot be excluded, although study-sensitive questions were provided in multiple ways. The absence of a control group (sham group; e.g. patients undergoing specific diagnostic laparoscopy without treatment) is a further limitation of the study. WIDER IMPLICATIONS OF THE FINDINGS: Our study shows that indicated minimally invasive surgery has a clear positive effect on the wellbeing and working performance of women suffering from moderate to severe endometriosis. Furthermore, national net savings in indirect costs with the present number of surgeries is estimated to be €10.7 million per year. In an idealized setting (i.e. without any diagnosis delay) this figure could be more than doubled. STUDY FUNDING/COMPETING INTERESTS: The study was performed on behalf of the University Hospital of Bern (Inselspital) as one of the leading Swiss tertiary care centers. The authors do not declare any competing interests.

HIV-associated malignancies among children attending the Baylor Clinic in Kampala, Uganda

Introduction: HIV-associated malignancies such as Kaposi’s sarcoma and Non-Hodgkin’s lymphoma occur in children and usually lead to significant morbidity and mortality. No studies have been done to establish prevalence and outcome of these malignancies in children in a hospital setting in Uganda. ^ Research question: What proportion of children attending the Baylor-Uganda COE present with HIV-associated malignancies and what are the characteristics and outcome of these malignancies? The objective was to determine the prevalence, associated factors and outcome of HIV-associated malignancies among children attending the Baylor-Uganda Clinic in Kampala, Uganda. Study Design: This was a retrospective case series involving records review of patients who presented to the Baylor-Clinic between January 2004 and December 2008. Study Setting: The Baylor-Uganda Clinic, where I worked as a physician before coming to Houston, is a well funded, well staffed; Pediatric HIV clinic located in Mulago Hospital, Kampala, Uganda and is affiliated to Makerere University Medical School. Study Participants: Medical charts of patients aged 6 weeks to 18 years who enrolled for care at the clinic during the years 2004 to 2008 were retrieved for data abstraction. Selection Criteria: Study participants had to be patients of Baylor-Uganda seen during the study period; they had to be aged 6 weeks to 18 years; and had to be HIV positive. Patients with incomplete data or whose malignancies were not confirmed by histology were excluded. Study Variables: Data on patient’s age, sex, diagnosis, type of malignancy, anatomic location of the malignancy; pathology report, baseline laboratory results and outcome of treatment, were abstracted. Data Analysis: Cross tabulation to determine associations between variables using Pearson’s chi square at 95% level of significance was done. Proportions of malignancies among different groups were determined. In addition, Kaplan Meier survival analysis and comparison of survival distributions using the log-rank test was done. Change in CD4 percentages from baseline was assessed with the Wilcoxon signed rank test. Results: The proportion of children with malignancies during the study period was found to be 1.65%. Only 2 malignancies: Kaposi’s sarcoma and Non-Hodgkin’s lymphoma were found. 90% of the malignancies were Kaposi’s sarcoma. Lymph node involvement in children with Kaposi’s sarcoma was common, but the worst prognosis was seen with visceral involvement. Deaths during follow-up were seen in the first few weeks to months. Upon starting treatment the CD4 cell percentage increased significantly from a baseline median of 6% to 14% at 6 months and 15.8% at 12 months of follow-up.^

Level II reliability methods for tunnels

In tunnel construction, as in every engineering work, it is usual the decision making, with incomplete data. Nevertheless, consciously or not, the builder weighs the risks (even if this is done subjectively) so that he can offer a cost. The objective of this paper is to recall the existence of a methodology to treat the uncertainties in the data so that it is possible to see their effect on the output of the computational model used and then to estimate the failure probability or the safety margin of a structure. In this scheme it is possible to include the subjective knowledge on the statistical properties of the random variables and, using a numerical model consistent with the degree of complexity appropiate to the problem at hand, to make rationally based decisions. As will be shown with the method it is possible to quantify the relative importance of the random variables and, in addition, it can be used, under certain conditions, to solve the inverse problem. It is then a method very well suited both to the project and to the control phases of tunnel construction.

Application of Bayesian approach in geotechnical engineering

En esta Tesis Doctoral se emplean y desarrollan Métodos Bayesianos para su aplicación en análisis geotécnicos habituales, con un énfasis particular en (i) la valoración y selección de modelos geotécnicos basados en correlaciones empíricas; en (ii) el desarrollo de predicciones acerca de los resultados esperados en modelos geotécnicos complejos. Se llevan a cabo diferentes aplicaciones a problemas geotécnicos, como es el caso de: (1) En el caso de rocas intactas, se presenta un método Bayesiano para la evaluación de modelos que permiten estimar el módulo de Young a partir de la resistencia a compresión simple (UCS). La metodología desarrollada suministra estimaciones de las incertidumbres de los parámetros y predicciones y es capaz de diferenciar entre las diferentes fuentes de error. Se desarrollan modelos "específicos de roca" para los tipos de roca más comunes y se muestra cómo se pueden "actualizar" esos modelos "iniciales" para incorporar, cuando se encuentra disponible, la nueva información específica del proyecto, reduciendo las incertidumbres del modelo y mejorando sus capacidades predictivas. (2) Para macizos rocosos, se presenta una metodología, fundamentada en un criterio de selección de modelos, que permite determinar el modelo más apropiado, entre un conjunto de candidatos, para estimar el módulo de deformación de un macizo rocoso a partir de un conjunto de datos observados. Una vez que se ha seleccionado el modelo más apropiado, se emplea un método Bayesiano para obtener distribuciones predictivas de los módulos de deformación de macizos rocosos y para actualizarlos con la nueva información específica del proyecto. Este método Bayesiano de actualización puede reducir significativamente la incertidumbre asociada a la predicción, y por lo tanto, afectar las estimaciones que se hagan de la probabilidad de fallo, lo cual es de un interés significativo para los diseños de mecánica de rocas basados en fiabilidad. (3) En las primeras etapas de los diseños de mecánica de rocas, la información acerca de los parámetros geomecánicos y geométricos, las tensiones in-situ o los parámetros de sostenimiento, es, a menudo, escasa o incompleta. Esto plantea dificultades para aplicar las correlaciones empíricas tradicionales que no pueden trabajar con información incompleta para realizar predicciones. Por lo tanto, se propone la utilización de una Red Bayesiana para trabajar con información incompleta y, en particular, se desarrolla un clasificador Naïve Bayes para predecir la probabilidad de ocurrencia de grandes deformaciones (squeezing) en un túnel a partir de cinco parámetros de entrada habitualmente disponibles, al menos parcialmente, en la etapa de diseño. This dissertation employs and develops Bayesian methods to be used in typical geotechnical analyses, with a particular emphasis on (i) the assessment and selection of geotechnical models based on empirical correlations; on (ii) the development of probabilistic predictions of outcomes expected for complex geotechnical models. Examples of application to geotechnical problems are developed, as follows: (1) For intact rocks, we present a Bayesian framework for model assessment to estimate the Young’s moduli based on their UCS. Our approach provides uncertainty estimates of parameters and predictions, and can differentiate among the sources of error. We develop ‘rock-specific’ models for common rock types, and illustrate that such ‘initial’ models can be ‘updated’ to incorporate new project-specific information as it becomes available, reducing model uncertainties and improving their predictive capabilities. (2) For rock masses, we present an approach, based on model selection criteria to select the most appropriate model, among a set of candidate models, to estimate the deformation modulus of a rock mass, given a set of observed data. Once the most appropriate model is selected, a Bayesian framework is employed to develop predictive distributions of the deformation moduli of rock masses, and to update them with new project-specific data. Such Bayesian updating approach can significantly reduce the associated predictive uncertainty, and therefore, affect our computed estimates of probability of failure, which is of significant interest to reliability-based rock engineering design. (3) In the preliminary design stage of rock engineering, the information about geomechanical and geometrical parameters, in situ stress or support parameters is often scarce or incomplete. This poses difficulties in applying traditional empirical correlations that cannot deal with incomplete data to make predictions. Therefore, we propose the use of Bayesian Networks to deal with incomplete data and, in particular, a Naïve Bayes classifier is developed to predict the probability of occurrence of tunnel squeezing based on five input parameters that are commonly available, at least partially, at design stages.

COMPETÊNCIAS ORGANIZACIONAIS EM UM MERCADO REGULADO: A CONTRIBUIÇÃO DO SISTEMA DE INFORMAÇÕES DE BENEFICIÁRIOS DA ANS

A presente dissertação tem como objetivo estudar a contribuição do Sistema de Informação de Beneficiários da Agência Nacional de Saúde Suplementar SIB/ANS para a formação e o desenvolvimento de competências organizacionais junto às empresas operadoras de planos de saúde, necessárias para se adequarem á um mercado regulado. A pesquisa teve caráter descritivo e etapa qualitativa, com análise bibliográfica e documental, quantitativa, mediante levantamento de dados de beneficiários relacionados a 27 (vinte e sete) operadoras de planos de saúde sediadas no ABCD paulista. Realizou-se análise descritiva da importância para as empresas dos dados de beneficiários em relação às competências sobre o processo, técnica e sobre a organização. Observou-se que nas duas primeiras competências analisadas, de uma tendência de melhoria, sendo que na última competência analisada, fica a esperar por melhoria de resultado, uma vez que demonstra que falta integração entre os dados e informações sobre os usuários das empresas integrantes da amostra, além da existência de dados incompletos e do uso de procedimentos inadequados para suprir essa deficiência (grande freqüência de dados repetidos). Conclui-se que, como a finalidade do SIB é identificar o beneficiário e o plano de saúde por ele contratado, e somente 37% das OPS conseguiram atender a contento, sob os diferentes eixos de avaliação desta competência, os requisitos básicos dos objetivos do SIB não foram alcançados e/ou entendidos pelos 63% das demais operadoras, indicando que as operadoras de planos de saúde devem se atentar para os significados que pretendeu-se apresentar no presente trabalho, como forma de melhorarem seu desempenho e, conseqüentemente, sua competitividade em um mercado regulado.(AU)

COMPETÊNCIAS ORGANIZACIONAIS EM UM MERCADO REGULADO: A CONTRIBUIÇÃO DO SISTEMA DE INFORMAÇÕES DE BENEFICIÁRIOS DA ANS

A presente dissertação tem como objetivo estudar a contribuição do Sistema de Informação de Beneficiários da Agência Nacional de Saúde Suplementar SIB/ANS para a formação e o desenvolvimento de competências organizacionais junto às empresas operadoras de planos de saúde, necessárias para se adequarem á um mercado regulado. A pesquisa teve caráter descritivo e etapa qualitativa, com análise bibliográfica e documental, quantitativa, mediante levantamento de dados de beneficiários relacionados a 27 (vinte e sete) operadoras de planos de saúde sediadas no ABCD paulista. Realizou-se análise descritiva da importância para as empresas dos dados de beneficiários em relação às competências sobre o processo, técnica e sobre a organização. Observou-se que nas duas primeiras competências analisadas, de uma tendência de melhoria, sendo que na última competência analisada, fica a esperar por melhoria de resultado, uma vez que demonstra que falta integração entre os dados e informações sobre os usuários das empresas integrantes da amostra, além da existência de dados incompletos e do uso de procedimentos inadequados para suprir essa deficiência (grande freqüência de dados repetidos). Conclui-se que, como a finalidade do SIB é identificar o beneficiário e o plano de saúde por ele contratado, e somente 37% das OPS conseguiram atender a contento, sob os diferentes eixos de avaliação desta competência, os requisitos básicos dos objetivos do SIB não foram alcançados e/ou entendidos pelos 63% das demais operadoras, indicando que as operadoras de planos de saúde devem se atentar para os significados que pretendeu-se apresentar no presente trabalho, como forma de melhorarem seu desempenho e, conseqüentemente, sua competitividade em um mercado regulado.(AU)

An Incremental EM-based Learning Approach for On-Line Prediction of Hospital Resource Utilization

Objective: Inpatient length of stay (LOS) is an important measure of hospital activity, health care resource consumption, and patient acuity. This research work aims at developing an incremental expectation maximization (EM) based learning approach on mixture of experts (ME) system for on-line prediction of LOS. The use of a batchmode learning process in most existing artificial neural networks to predict LOS is unrealistic, as the data become available over time and their pattern change dynamically. In contrast, an on-line process is capable of providing an output whenever a new datum becomes available. This on-the-spot information is therefore more useful and practical for making decisions, especially when one deals with a tremendous amount of data. Methods and material: The proposed approach is illustrated using a real example of gastroenteritis LOS data. The data set was extracted from a retrospective cohort study on all infants born in 1995-1997 and their subsequent admissions for gastroenteritis. The total number of admissions in this data set was n = 692. Linked hospitalization records of the cohort were retrieved retrospectively to derive the outcome measure, patient demographics, and associated co-morbidities information. A comparative study of the incremental learning and the batch-mode learning algorithms is considered. The performances of the learning algorithms are compared based on the mean absolute difference (MAD) between the predictions and the actual LOS, and the proportion of predictions with MAD < 1 day (Prop(MAD < 1)). The significance of the comparison is assessed through a regression analysis. Results: The incremental learning algorithm provides better on-line prediction of LOS when the system has gained sufficient training from more examples (MAD = 1.77 days and Prop(MAD < 1) = 54.3%), compared to that using the batch-mode learning. The regression analysis indicates a significant decrease of MAD (p-value = 0.063) and a significant (p-value = 0.044) increase of Prop(MAD