Uma feira de idéias.

bitstream/item/128296/1/EDUFA-FEIRA.pdf1. ed.Projeto Minibibliotecas

Amigos por natureza.

bitstream/item/128289/1/EDUFA-AMIGOS-NATUREZA.pdfIlustrações Leonardo Branco. Projeto Minibibliotecas

Segredos da Serra dos Macacos.

bitstream/item/128293/1/EDUFA-SERRA-MACACOS.pdf1. ed.Projeto Minibibliotecas

Fisgando oportunidades.

bitstream/item/128287/1/EDUFA-FISGANDO.pdf1. ed.Projeto Minibibliotecas

Esta é uma outra história.

bitstream/item/128292/1/EDUFA-HISTORIA.pdfProjeto Minibibliotecas

Influence diagnostics in exponentiated-Weibull regression models with censored data.

Diagnostic methods have been an important tool in regression analysis to detect anomalies, such as departures from the error assumptions and the presence of outliers and influential observations with the fitted models. The literature provides plenty of approaches for detecting outlying or influential observations in data sets. In this paper, we follow the local influence approach (Cook 1986) in detecting influential observations with exponentiated-Weibull regression models. The relevance of the approach is illustrated with a real data set, where it is shown that by removing the most influential observations, there is a change in the decision about which model fits the data better.Peer Reviewe

Influence diagnostics in exponentiated-Weibull regression models with censored data

Diagnostic methods have been an important tool in regression analysis to detect anomalies, such as departures from the error assumptions and the presence of outliers and influential observations with the fitted models. The literature provides plenty of approaches for detecting outlying or influential observations in data sets. In this paper, we follow the local influence approach (Cook 1986) in detecting influential observations with exponentiated-Weibull regression models. The relevance of the approach is illustrated with a real data set, where it is shown that by removing the most influential observations, there is a change in the decision about which model fits the data better

Patients’ and physicians’ perceptions of teleconsultations

Funding Information: The Regional Health Administration of Lisbon and Tagus Valley funded Dr. Maria's salary and had no role in the study design, data collection, analysis or writing of this article. The present publication was funded by Fundação Ciência e Tecnologia, IP national support through CHRC (UIDP/04923/2020). Publisher Copyright: © The Author(s) 2022.Introduction: Previous qualitative research on teleconsultations has focused on synchronous communication between a patient and a clinician. This study aims to explore physicians' and patients' perceptions of the interaction on the interface between primary care and the Cardiology service of a referral hospital through teleconsultations. Methods: This qualitative study was embedded in an organizational case study concerning the introduction and rollout of a new service model that took place at the point of care. The patients and physicians were recruited for semi-structured interviews until thematic saturation was achieved, between September 2019 - January 2020. The interviews were audiorecorded and anonymized. The transcribed interviews were stored, coded, and analyzed in MAXQDA, following the steps for conventional content analysis. Results: A total of 29 participants were interviewed. Patients and physicians presented clear views about the role of the GP and the cardiologist and their function in overall structure of healthcare. GPs felt their role was to bring expertise in the patient which could supplement the cardiologists' expertise on the condition. However, GPs had to renegotiate roles in the teleconsultations when they saw themselves in a new situation, together with another physician and the patient. Conclusions: Our findings suggest that joint teleconsultations can promote continuity of care for patients in the primary/secondary care interface. Active coordination between physicians with delineation of roles throughout primary-secondary care interface is needed to manage selected patients who may benefit the most from shared care.publishersversionpublishe

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.Comment: 12 pages. Statistical Paper