1,721,150 research outputs found
A Bayesian decision-theoretic model of sequential experimentation with delayed response
Full text linkWe propose a Bayesian decision theoretic model of a fully sequential experiment in which the real-valued primary end point is observed with delay. The goal is to identify the sequential experiment which maximizes the expected benefits of technology adoption decisions, minus sampling costs. The solution yields a unified policy defining the optimal ‘do not experiment’–‘fixed sample size experiment’–‘sequential experiment’ regions and optimal stopping boundaries for sequential sampling, as a function of the prior mean benefit and the size of the delay. We apply the model to the field of medical statistics, using data from published clinical trials
A Bayesian Decision-Theoretic Model of Sequential Experimentation with Delayed Response
No full textWe solve a Bayesian decision-theoretic model of a sequential experiment in which the real-valued primary end point is observed with delay. The solution yields a unified policy defining the optimal 'do notexperiment'/'fixed sample size experiment'/'sequential experiment' regions as a function of the prior mean. The model can value the expected benefits accruing to study units, the fixed costs of switching from control to treatment, and allows the number of study units to benefit from a stopping decision to fall as the number of study units recruited to the experiment rises. We apply the model to the field of medical statistics, using data from a published trial investigating the clinical- and cost-effectiveness of drug-eluting stents versus bare metal stents. We demonstrate the model’s superiority over alternative trial designs when judged according to the maximisation of the net benefits of the trial, minus sampling costs, and we investigate how the size of the delay determines the optimal choice of trial design. The optimal policy also performs well when judged according to the probability of making the correct selection of health technology
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
Optimal Decision Rules for HTA Under Uncertainty: a Wider, Dynamic Perspective
No full textWe present a two period framework which combines real option and decision-theoretic approaches to health technology assessment (HTA) under uncertainty. By viewing adoption, treatment and research decisions as a single economic project, we illustrate how their key dimensions affect optimal rules. We consider the results in relation to the existing literature and argue that developments in this direction could contribute substantially to efficiency gains in resource allocation
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
Value-based clinical trials:selecting recruitment rates and trial lengths in different regulatory contexts
Full text linkHealth systems are placing increasing emphasis on improving the design and operation of clinical trials, with
the aim of making the health technology adoption process more value-based. We present a model of a valuebased
two-armed clinical trial in which both the recruitment rate and trial length are optimized. The model
is value-based because it balances the cost of the trial with the expected benefit it generates for patients,
valued by the relative health benefits and costs of the technologies. We consider a wide range of regulatory
and practical contexts which address how patient health is valued (discount rate, time horizon, pragmatic
trials). We present comparative statics and asymptotic analysis, together with a retrospective application
to a recent health technology assessment, and an extension for adaptive trials. Results challenge traditional
perceptions concerning the efficiency, length, and knowledge that may be gained from clinical research for
trial managers or funders charged with delivering value efficiently: we highlight trade-offs between trial
costs and population health benefits influenced by trial outcomes and the importance of optimizing both
recruitment rate and trial duration rather than sample size alone
Optimal Sequential Sampling with Delayed Observations and Unknown Variance
No full textSequential stochastic optimization has been used in many contexts, from simulation, to e-commerce, to clinical trials. Much of this analysis assumes that observations are made soon after a sampling decision is made, so that the next sampling decision can benefit from the most recent data. This assumption is not true in a number of contexts, including clinical trials. In this paper we extend sequential sampling tools from simulation optimization to be useful when there exists a delay in observing the data from sampling, with a specific focus on the situation in which the sampling variance is unknown. We demonstrate the benefits of doing so by benchmarking the optimization algorithms with data from a published clinical trial
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