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Author : Harald Atmanspacher
ISBN : 9781118864777
Genre : Mathematics
File Size : 86.26 MB
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2017 PROSE Award Honorable Mention The PROSE Awards draw attention to pioneering works of research and for contributions to the conception, production, and design of landmark works in their fields. Featuring peer-reviewed contributions from noted experts in their fields of research, Reproducibility: Principles, Problems, Practices, and Prospects presents state-of-the-art approaches to reproducibility, the gold standard of sound science, from multi- and interdisciplinary perspectives. Including comprehensive coverage for implementing and reflecting the norm of reproducibility in various pertinent fields of research, the book focuses on how the reproducibility of results is applied, how it may be limited, and how such limitations can be understood or even controlled in the natural sciences, computational sciences, life sciences, social sciences, and studies of science and technology. The book presents many chapters devoted to a variety of methods and techniques, as well as their epistemic and ontological underpinnings, which have been developed to safeguard reproducible research and curtail deficits and failures. The book also investigates the political, historical, and social practices that underlie reproducible research in contemporary science studies, including the difficulties of good scientific practice and the ethos of reproducibility in modern innovation societies. Reproducibility: Principles, Problems, Practices, and Prospects is a guide for researchers who are interested in the general and overarching questions behind the concept of reproducibility; for active scientists who are confronted with practical reproducibility problems in their everyday work; and for economic stakeholders and political decision makers who need to better understand the challenges of reproducibility. In addition, the book is a useful in-depth primer for undergraduate and graduate-level courses in scientific methodology and basic issues in the philosophy and sociology of science from a modern perspective. “A comprehensive, insightful treatment of the reproducibility challenges facing science today and of ways in which the scientific community can address them.” Kathleen Hall Jamieson, Elizabeth Ware Packard Professor of Communication, University of Pennsylvania “How can we make sure that reproducible research remains a key imperative of scientific communication under increasing commercialization, media attention, and publication pressure? This handbook offers the first interdisciplinary and fundamental treatment of this important question.”Torsten Hothorn, Professor of Biostatistics, University of Zurich Harald Atmanspacher, PhD, is Associate Fellow and staff member at Collegium Helveticum, ETH and University Zurich and is also President of the Society for Mind-Matter Research. He has pioneered advances in complex dynamical systems research and in a number of topics concerned with the relation between the mental and physical. Sabine Maasen, PhD, is Professor for Sociology of Science and Director of the Munich Center for Technology in Society (TU Munich) and Associate Fellow at Collegium Helveticum (ETH and University Zurich). Her research focuses on the interface of science, technology, and society, notably with respect to neuroscience and its applications.
Category: Mathematics

Statistical Challenges In Assessing And Fostering The Reproducibility Of Scientific Results

Author : National Academies of Sciences, Engineering, and Medicine
ISBN : 9780309392051
Genre : Mathematics
File Size : 28.26 MB
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Questions about the reproducibility of scientific research have been raised in numerous settings and have gained visibility through several high-profile journal and popular press articles. Quantitative issues contributing to reproducibility challenges have been considered (including improper data measurement and analysis, inadequate statistical expertise, and incomplete data, among others), but there is no clear consensus on how best to approach or to minimize these problems. A lack of reproducibility of scientific results has created some distrust in scientific findings among the general public, scientists, funding agencies, and industries. While studies fail for a variety of reasons, many factors contribute to the lack of perfect reproducibility, including insufficient training in experimental design, misaligned incentives for publication and the implications for university tenure, intentional manipulation, poor data management and analysis, and inadequate instances of statistical inference. The workshop summarized in this report was designed not to address the social and experimental challenges but instead to focus on the latter issues of improper data management and analysis, inadequate statistical expertise, incomplete data, and difficulties applying sound statistic inference to the available data. Many efforts have emerged over recent years to draw attention to and improve reproducibility of scientific work. This report uniquely focuses on the statistical perspective of three issues: the extent of reproducibility, the causes of reproducibility failures, and the potential remedies for these failures.
Category: Mathematics

Implementing Reproducible Research

Author : Victoria Stodden
ISBN : 9781466561601
Genre : Mathematics
File Size : 57.45 MB
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In computational science, reproducibility requires that researchers make code and data available to others so that the data can be analyzed in a similar manner as in the original publication. Code must be available to be distributed, data must be accessible in a readable format, and a platform must be available for widely distributing the data and code. In addition, both data and code need to be licensed permissively enough so that others can reproduce the work without a substantial legal burden. Implementing Reproducible Research covers many of the elements necessary for conducting and distributing reproducible research. It explains how to accurately reproduce a scientific result. Divided into three parts, the book discusses the tools, practices, and dissemination platforms for ensuring reproducibility in computational science. It describes: Computational tools, such as Sweave, knitr, VisTrails, Sumatra, CDE, and the Declaratron system Open source practices, good programming practices, trends in open science, and the role of cloud computing in reproducible research Software and methodological platforms, including open source software packages, RunMyCode platform, and open access journals Each part presents contributions from leaders who have developed software and other products that have advanced the field. Supplementary material is available at
Category: Mathematics

From One Environment To Many

Author : Jinguang Lin
ISBN : OCLC:1077475406
Genre :
File Size : 65.67 MB
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When the same experiment is carried out in a different environment, the error term not only includes the random error within a given experiment, but it also includes the additional sources of variability that are introduced by conducting the same experiment in different environments. These differences include both natural factors such as location, time or weather and other factors such as personnel or equipment necessary to carry out this experiment. By considering the effect of changing experimental environments on the reproducibility of experiments, we try to figure out in what situations the initial experimental results will likely carry over to other environments. We examine how p-value, effect size, sample size, and the ratio of the standard deviation of environment by treatment interaction and the standard deviation of experimental error interact with one another, and as a whole, affect the experiment's reproducibility. We suggest that not only p-values but also the effect sizes and the environmental effect ratio---the ratio of the standard deviation of environment by treatment interaction and the standard deviation of experimental error---should be considered when researchers are making statistical inferences. Large effect sizes and/or small ratios of the environmental effect ratio favor high probability of reproducibility. If the environmental effect ratio is too large, the reproducibility probability may be reduced to just a coin toss, and if effect sizes are small, researchers should be very cautious about making inferences about reproducibility even if the observed p-value is small and sample size is large.

Principles Of Nutritional Assessment

Author : Rosalind S. Gibson
ISBN : 9780195171693
Genre : Medical
File Size : 81.96 MB
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This is a comprehensive text on the methods - dietary, anthropometric, laboratory and clinical - of assessing the nutritional status of populations and of individuals in the hospital or the community. This Second Edition incorporates recent data from national nutritional surveys in the US and Europe; the flood of new information about iron, vitamin A and iodine; the role of folate in preventing neural tube defects; the use of HPLC techniques and enzyme assays; improvements in data handling; and many other developments. A paperback edition of this book is available to readers living outside of North America and Europe. Interested parties should contact the author at: [email protected] http: //
Category: Medical