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Lisbon, Portugal

Background Cost fluctuations render the outcome of any treatment switch uncertain, so that decision makers might have to wait for more information before optimally switching treatments, especially when the incremental cost per quality-adjusted life year (QALY) gained cannot be fully recovered later on. Objective To analyze the timing of treatment switch under cost uncertainty. Methods A dynamic stochastic model for the optimal timing of a treatment switch is developed and applied to a problem in medical decision taking, i.e. to patients with unresectable gastrointestinal stromal tumour (GIST). Results The theoretical model suggests that cost uncertainty reduces expected net benefit. In addition, cost volatility discourages switching treatments. The stochastic model also illustrates that as technologies become less cost competitive, the cost uncertainty becomes more dominant. With limited substitutability, higher quality of technologies will increase the demand for those technologies disregarding the cost uncertainty. The results of the empirical application suggest that the first-line treatment may be the better choice when considering lifetime welfare. Conclusions Under uncertainty and irreversibility, low-risk patients must begin the second-line treatment as soon as possible, which is precisely when the second-line treatment is least valuable. As the costs of reversing current treatment impacts fall, it becomes more feasible to provide the option-preserving treatment to these low-risk individuals later on. © 2014 International Society for Pharmacoeconomics and Outcomes Research (ISPOR). Published by Elsevier Inc. Source

Martins L.F.,ISCTE IUL | Martins L.F.,University of Surrey | Gabriel V.J.,University of Surrey
Computational Statistics and Data Analysis | Year: 2014

Model averaging (MA) estimators in the linear instrumental variables regression framework are considered. The obtaining of weights for averaging across individual estimates by direct smoothing of selection criteria arising from the estimation stage is proposed. This is particularly relevant in applications in which there is a large number of candidate instruments and, therefore, a considerable number of instrument sets arising from different combinations of the available instruments. The asymptotic properties of the estimator are derived under homoskedastic and heteroskedastic errors. A simple Monte Carlo study contrasts the performance of MA procedures with existing instrument selection procedures, showing that MA estimators compare very favorably in many relevant setups. Finally, this method is illustrated with an empirical application to returns to education. © 2013 Elsevier B.V. All rights reserved. Source

Conceicao O.,University of Minho | Fontes M.,National Laboratory of Energy and Geology | Calapez T.,ISCTE IUL
Technovation | Year: 2012

This paper addresses the commercialisation decisions of research-based spin-off firms (RBSOs), focusing on the case of companies specialising in the production and sale of intellectual property - a model of entrepreneurial behaviour increasingly frequent in science-based fields and that research-based spin-offs may be more prone to adopt, given their specific characteristics. Combining insights from the economics of technological change and the strategic management of technology literature, we discuss the conditions that can influence firms ability to operate in the market for technology, and advance some theory-driven hypotheses regarding key factors that are likely to determine it nature of knowledge being exploited, appropriability conditions, location and degree of control upon complementary assets and institutional setting of origin as well as their impact upon firms decisions. These hypotheses are tested on a group of 80 European RBSOs, using data collected specifically for this purpose, on the basis of questionnaire-based interviews. This research adds to recent work on the determinants of the commercialisation strategy of technology-based SMEs, but by focusing on a particular group of companies the RBSOs we also take into consideration some distinctive characteristics of this group, which introduce some specificity in their innovative behaviour. © 2011 Elsevier Ltd. All rights reserved. Source

Guerreiro J.,ISCTE IUL | Trigueiros D.,University of Algarve
Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) | Year: 2010

Support Vector Machines (SVM) are believed to be as powerful as Artificial Neural Networks (ANN) in modeling complex problems while avoiding some of the drawbacks of the latter such as local minimæ or reliance on architecture. However, a question that remains to be answered is whether SVM users may expect improvements in the interpretability of their models, namely by using rule extraction methods already available to ANN users. This study successfully applies the Orthogonal Search-based Rule Extraction algorithm (OSRE) to Support Vector Machines. The study evidences the portability of rules extracted using OSRE, showing that, in the case of SVM, extracted rules are as accurate and consistent as those from equivalent ANN models. Importantly, the study also shows that the OSRE method benefits from SVM specific characteristics, being able to extract less rules from SVM than from equivalent ANN models. © 2010 Springer-Verlag. Source

ACM International Conference Proceeding Series | Year: 2011

In this paper we do a review of research in software and game development, game modding communities, open-source development and open content creation. The ideas gathered in this research used to create a conceptual model for the creation of a collaborative on-line framework for browser games development. The generated conceptual model will be used in future work to build and test the framework. © 2011 ACM. Source

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