1,721,230 research outputs found
The Gini test for survival data in presence of small and unbalanced groups
No full textThe aim of this note is to study the performance of the Gini concentration test for survival data introduced in Bonetti et al. (2009) in
presence of unbalanced and small samples. We compared the performance of the asymptotic test with an alternative permutation distribution test, illustrating by simulation that if groups are very small the
latter test should be used. Also, we show how the denition of the
length of time considered in the construction of the test statistic can
be chosen to improve the performance of the test
Patterns of treatment effects in subsets of patients in clinical trials
No full textWe discuss the practice of examining patterns of treatment effects across overlapping patient subpopulations. In particular, we focus on the case in which patient subgroups are defined to contain patients having increasingly larger (or smaller) values of one particular covariate of interest, with the intent of exploring the possible interaction between treatment effect and that covariate. We formalize these subgroup approaches (STEPP: subpopulation treatment effect pattern plots) and implement them when treatment effect is defined as the difference in survival at a fixed time point between two treatment arms. The joint asymptotic distribution of the treatment effect estimates is derived, and used to construct simultaneous confidence bands around the estimates and to test the null hypothesis of no interaction. These methods are illustrated using data from a clinical trial conducted by the International Breast Cancer Study Group, which demonstrates the critical role of estrogen receptor content of the primary breast cancer for selecting appropriate adjuvant therapy. The considerations are also relevant for general subset analysis, since information from the same patients is typically used in the estimation of treatment effects within two or more subgroups of patients defined with respect to different covariates. © Oxford University Press 2004; all rights reserved
Going Beyond Counting First Authors in Author Co-citation Analysis
Full text linkThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
Higher Education and Universal Design in Tanzania. A New Model of Inclusion and Sustainable Development
No full text: The need to create a more inclusive society in Tanzania is confronted with a discrepancy between the aims of a regulatory framework, aimed at making Higher Education spaces inclusive, and the question of the right of access to built environments, particularly in universities. The study presents the pilot case of the RUCU's Learning Center for Disabilities to demonstrate that the combination of UDL, architectural accessibility and international cooperation can give impetus to new research and application themes, creating innovative models and good practices to be disseminated for a new shared awareness
Variations on the Author
Full text link“Variations on the Author” discusses two of Eduardo Coutinho’s recent films (Um Dia na Vida, from 2010, and Últimas Conversas, posthumously released in 2015) and their contribution to the general question of documentary authorship. The director’s filmography is characterized by a consistent yet self-effacing form of authorial self-inscription: Coutinho often features as an interviewer that rather than express opinions propels discourses; an interviewer that is good at listening. This mode of self-inscription characterizes him as an author who is not expressive but who is nonetheless markedly present on the screen. In Um Dia na Vida, however, Coutinho is completely absent form the image, while Últimas Conversas, on the contrary, includes a confessional prologue that moves the director from the margins to the center of his films. This article examines the ways in which these works stand out in the filmography of a director who offers new insights into the notion of cinematic authorship
Appropriate Similarity Measures for Author Cocitation Analysis
Full text linkWe provide a number of new insights into the methodological discussion about author cocitation analysis. We first argue that the use of the Pearson correlation for measuring the similarity between authors’ cocitation profiles is not very satisfactory. We then discuss what kind of similarity measures may be used as an alternative to the Pearson correlation. We consider three similarity measures in particular. One is the well-known cosine. The other two similarity measures have not been used before in the bibliometric literature. Finally, we show by means of an example that our findings have a high practical relevance.information science;Pearson correlation;cosine;similarity measure;author cocitation analysis
The Nine Milestones of the Italian Federation of Ozone Therapy.
No full textThe Italian Federation of Oxygen-Ozone Therapy (FIO) was founded on 14th June 2003 with the organization of the first FIO National Congress held at the University of Florence under
the direction of Gianni Pellicanò
Risk-averse optimization of reward-based coherent risk measures
No full textIn real-world problems such as robotics, finance and healthcare, randomness is always present, thus, it is important to take risk into consideration in order to limit the chance of rare but dangerous events. The literature on risk-averse reinforcement learning has produced many different approaches to tackle the problem, but they either struggle to scale up to complex instances, or they exhibit irrational behaviors. Here we present two novel risk-averse objectives that are both coherent and easy to optimize: the reward-based mean-mean absolute deviation (Mean-RMAD) and the reward-based conditional value at risk (RCVaR). Instead of reducing the return risk, these measures minimize the per-step reward one. We prove that these risk measures bound the corresponding return-based risk measures, so that they can be also used as proxies for their return-based versions. We develop safe algorithms for these risk measures with guaranteed monotonic improvement, and their practical trust-region versions. Furthermore, we propose a decomposition for the RCVaR optimization problem into a sequence of risk-neutral problems. Finally, we conduct an empirical analysis on the introduced approaches, demonstrating their effectiveness in retrieving a variety of risk-averse behaviors on both toy problems and more challenging ones, such as a simulated trading environment and robotic locomotion tasks
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