The application of the antidumping instrument by WTO members is often controversial because of the protectionist character of these measures where inefficient industries are protected from foreign competition. The legal framework within the WTO has loopholes that leave wide discretion to the investigating authorities to determine that a product is dumped, thereby emphasizing the protectionist nature of antidumping. The use of antidumping becomes even more controversial when WTO members use the antidumping tool beyond the legal scope of WTO law. The questions raised in this book concern the EU dumping determinations and their conformity with WTO law. This thought-provoking work examines whether European Union legislation on dumping, the practices adopted by the European Commission and the Council, as well as the decisions by the EC courts are in conformity with WTO law. The author's findings are particularly relevant given the frequent use of antidumping measures by EU authorities, especially as relates to Asian countries, and he carefully documents areas where the EU infringes WTO law.
Multi-state models provide a statistical framework for studying longitudinal data on subjects when focus is on the occurrence of events that the subjects may experience over time. They find application particularly in biostatistics, medicine, and public health. The book includes mathematical detail which can be skipped by readers more interested in the practical examples. It is aimed at biostatisticians and at readers with an interest in the topic having a more applied background, such as epidemiology. This book builds on several courses the authors have taught on the subject. Key Features: · Intensity-based and marginal models. · Survival data, competing risks, illness-death models, recurrent events. · Includes a full chapter on pseudo-values. · Intuitive introductions and mathematical details. · Practical examples of event history data. · Exercises. Software code in R and SAS and the data used in the book can be found on the book’s webpage.
The covid-19 crisis accelerated virtual collaboration exponentially, creating an instant need for virtual facilitation skills. People and organizations have started on this journey, but do not yet have the experience and competencies to use this medium for effective and energetic collaboration. Virtual Facilitation will show you how to have successful virtual events, virtual meetings, virtual workshops and training. Packed full of tips, insights and real case studies, the author's practical approach to virtual facilitation will show you how to effectively learn the skills needed to suceed. This book will also cover: The role of the facilitator, and what is expected The design of the process How to avoid common mistakes Implementation and influencing behaviour Virtual Facilitation will show you how to plan for virtual events, how to develop skills to be able to host virtual meetings, virtual courses, virtual training, virtual workshops, and virtual larger events to meet 21st century needs.
Do you have data on occupant behaviour, indoor environment or energy use in buildings? Are you interested in statistical analysis and modelling? Do you have a specific (research) question and dataset and would like to know how to answer the question with the data available? Statistical Modelling of Occupant Behaviour covers a range of statistical methods and models used for modelling energy- and comfort-related occupant behaviour in buildings. It is a classical textbook on statistics, including many practical examples related to occupant behaviour that are either taken from real research problems or adapted from such. The main focus is traditional statistical techniques based on the likelihood principle that can be applied to occupant behaviour modelling, including: General, generalised linear and survival models Mixed effect and hierarchical models Linear time series and Markov models Linear state space and hidden Markov models Illustration of all methods using occupant behaviour examples implemented in R The built environment affects occupants who live and work in it, and occupants affect the built environment by adapting it to their needs – for example, by adapting their indoor environments by interacting with building components and systems. These adaptive behaviours account for great uncertainty in the prediction of building energy use and indoor environmental conditions. Occupant behaviour is complex and multi-disciplinary but can be successfully modelled using statistical approaches. Statistical Modelling of Occupant Behaviour is written for researchers and advanced practitioners who work with real-world applications and modelling of occupant data. It describes the kinds of statistical models that may be used in various occupant behaviour modelling research. It gives a theoretical overview of these methods and then applies them to the study of occupant behaviour using readily replaceable examples in the R environment that are based on actual and experimental data.
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