947 resultados para Dynamic data analysis


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BACKGROUND: The inherent complexity of statistical methods and clinical phenomena compel researchers with diverse domains of expertise to work in interdisciplinary teams, where none of them have a complete knowledge in their counterpart's field. As a result, knowledge exchange may often be characterized by miscommunication leading to misinterpretation, ultimately resulting in errors in research and even clinical practice. Though communication has a central role in interdisciplinary collaboration and since miscommunication can have a negative impact on research processes, to the best of our knowledge, no study has yet explored how data analysis specialists and clinical researchers communicate over time. METHODS/PRINCIPAL FINDINGS: We conducted qualitative analysis of encounters between clinical researchers and data analysis specialists (epidemiologist, clinical epidemiologist, and data mining specialist). These encounters were recorded and systematically analyzed using a grounded theory methodology for extraction of emerging themes, followed by data triangulation and analysis of negative cases for validation. A policy analysis was then performed using a system dynamics methodology looking for potential interventions to improve this process. Four major emerging themes were found. Definitions using lay language were frequently employed as a way to bridge the language gap between the specialties. Thought experiments presented a series of "what if" situations that helped clarify how the method or information from the other field would behave, if exposed to alternative situations, ultimately aiding in explaining their main objective. Metaphors and analogies were used to translate concepts across fields, from the unfamiliar to the familiar. Prolepsis was used to anticipate study outcomes, thus helping specialists understand the current context based on an understanding of their final goal. CONCLUSION/SIGNIFICANCE: The communication between clinical researchers and data analysis specialists presents multiple challenges that can lead to errors.

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Book review of: Chance Encounters: A First Course in Data Analysis and Inference by Christopher J. Wild and George A.F. Seber 2000, John Wiley & Sons Inc. Hard-bound, xviii + 612 pp ISBN 0-471-32936-3

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We present an analysis of the data from our Swedish-ESO Submillimetre Telescope molecular line survey in the 1.3 mm band of the N, M, and NW positions in the Sgr B2 molecular cloud. The line emissions from 42 molecular species, and some of their isotopomers, were analyzed assuming a single temperature and a homogeneous source. In cases where a source size much smaller than the antenna beam (23

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Dynamic mechanical analysis (DMA) is an analytical technique in which an oscillating stress is applied to a sample and the resultant strain measured as functions of both oscillatory frequency and temperature. From this, a comprehensive knowledge of the relationships between the various viscoelastic parameters, e.g. storage and loss moduli, mechanical damping parameter (tan delta), dynamic viscosity, and temperature may be obtained. An introduction to the theory of DMA and pharmaceutical and biomedical examples of the use of this technique are presented in this concise review. In particular, examples are described in which DMA has been employed to quantify the storage and loss moduli of polymers, polymer damping properties, glass transition temperature(s), rate and extent of curing of polymer systems, polymer-polymer compatibility and identification of sol-gel transitions. Furthermore, future applications of the technique for the optimisation of the formulation of pharmaceutical and biomedical systems are discussed. (C) 1999 Elsevier Science B.V. All rights reserved.