{"title":"Wiley Series In Computational And Quantitative Social Science","description":"\u003cp\u003eDelve into the Wiley Series, exploring the cutting edge of computational and quantitative methods in social science. Discover insightful research and groundbreaking techniques shaping our understanding of society.\u003c\/p\u003e","products":[{"product_id":"agent-based-models-and-causal-inference-book-gianluca-manzo-9781119704478","title":"Agent-based Models and Causal Inference","description":"Agent-based Models and Causal Inference   Scholars of causal inference have given little credence to the possibility that ABMs could be an important tool in warranting causal claims. Manzo’s book makes a convincing case that this is a mistake. The book starts by describing the impressive progress that ABMs have made as a credible methodology in the last several decades. It then goes on to compare the inferential threats to ABMs versus the traditional methods of RCTs, regression, and instrumental variables showing that they have a common vulnerability of being based on untestable assumptions. The book concludes by looking at four examples where an analysis based on ABMs complements and augments the evidence for specific causal claims provided by other methods. Manzo has done a most convincing job of showing that ABMs can be an important resource in any researcher’s tool kit. —Christopher Winship, Diker-Tishman Professor of Sociology, Harvard University, USA   Agent-based Models and Causal Inference is a first-rate contribution to the debate on, and practice of, causal claims. With exemplary rigor, systematic precision and pedagogic clarity, this book contrasts the assumptions about causality that undergird agent-based models, experimental methods, and statistically based observational methods, discusses the challenges these methods face as far as inferences go, and, in light of this discussion, elaborates the case for combining these methods’ respective strengths: a remarkable achievement. —Ivan Ermakoff, Professor of Sociology, University of Wisconsin-Madison, USA   Agent-based models are a uniquely powerful tool for understanding how patterns in society may arise in often surprising and counter-intuitive ways. This book offers a strong and deeply reflected argument for how ABM’s can do much more: add to actual empirical explanation. The work is of great value to all social scientists interested in learning how computational modelling can help unraveling the complexity of the real social world. —Andreas Flache, Professor of Sociology at the University of Groningen, Netherlands   Agent-based Models and Causal Inference is an important and much-needed contribution to sociology and computational social science. The book provides a rigorous new contribution to current understandings of the foundation of causal inference and justification in the social sciences. It provides a powerful and cogent alternative to standard statistical causal-modeling approaches to causation. Especially valuable is Manzo’s careful analysis of the conditions under which an agent-based simulation is relevant to causal inference. The book represents an exceptional contribution to sociology, the philosophy of social science, and the epistemology of simulations and models. —Daniel Little, Professor of philosophy, University of Michigan, USA   Agent-based Models and Causal Inference delivers an insightful investigation into the conditions under which different quantitative methods can legitimately hold to be able to establish causal claims. The book compares agent-based computational methods with randomized experiments, instrumental variables, and various types of causal graphs.   Organized in two parts, Agent-based Models and Causal Inference connects the literature from various fields, including causality, social mechanisms, statistical and experimental methods for causal inference, and agent-based computation models to help show that causality means different things within different methods for causal analysis, and that persuasive causal claims can only be built at the intersection of these various methods.   Readers will also benefit from the inclusion of:     A thorough comparison between agent-based computation models to randomized experiments, instrumental variables, and several types of causal graphs A compelling argument that observational and experimental methods are not qualitatively superior to simulation-based methods in their ability to establish causal claims Practical discussions of how statistical, experimental and computational methods can be combined to produce reliable causal inferences   Perfect for academic social scientists and scholars in the fields of computational social science, philosophy, statistics, experimental design, and ecology, Agent-based Models and Causal Inference will also earn a place in the libraries of PhD students seeking a one-stop reference on the issue of causal inference in agent-based computational models.","brand":"WoB","offers":[{"title":"GB \/ NEW \/ GARDNERS","offer_id":49737560391953,"sku":"NGR9781119704478","price":0.0,"currency_code":"GBP","in_stock":false},{"title":"US \/ NEW \/ INGRAM","offer_id":51105098367249,"sku":"NIN9781119704478","price":0.0,"currency_code":"GBP","in_stock":true},{"title":"GB \/ NEW \/ INGRAM","offer_id":52139795448081,"sku":"NLS9781119704478","price":0.0,"currency_code":"GBP","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0784\/4072\/6801\/files\/1119704472.jpg?v=1751048511"},{"product_id":"agent-based-modeling-of-tax-evasion-book-sascha-hokamp-9781119155683","title":"Agent-based Modeling of Tax Evasion","description":"The only single-source guide to understanding, using, adapting, and designing state-of-the-art agent-based modelling of tax evasion   A computational method for simulating the behavior of individuals or groups and their effects on an entire system, agent-based modeling has proven itself to be a powerful new tool for detecting tax fraud. While interdisciplinary groups and individuals working in the tax domain have published numerous articles in diverse peer-reviewed journals and have presented their findings at international conferences, until Agent-based Modelling of Tax Evasion there was no authoritative, single-source guide to state-of-the-art agent-based tax evasion modeling techniques and technologies.   Featuring contributions from distinguished experts in the field from around the globe, Agent-Based Modelling of Tax Evasion provides in-depth coverage of an array of field tested agent-based tax evasion models. Models are presented in a unified format so as to enable readers to systematically work their way through the various modeling alternatives available to them. Three main components of each agent-based model are explored in accordance with the Overview, Design Concepts, and Details (ODD) protocol, each section of which contains several sub elements that help to illustrate the model clearly and that assist readers in replicating the modeling results described.     Presents models in a unified and structured manner to provide a point of reference for readers interested in agent-based modelling of tax evasion Explores the theoretical aspects and diversity of agent-based modeling through the example of tax evasion Provides an overview of the characteristics of more than thirty agent-based tax evasion frameworks Functions as a solid foundation for lectures and seminars on agent-based modelling of tax evasion   The only comprehensive treatment of agent-based tax evasion models and their applications, this book is an indispensable working resource for practitioners and tax evasion modelers both in the agent-based computational domain and using other methodologies. It is also an excellent pedagogical resource for teaching tax evasion modeling and\/or agent-based modeling generally.","brand":"WoB","offers":[{"title":"US \/ VERY_GOOD \/ SBYB","offer_id":50377788457233,"sku":"CIN1119155681VG","price":0.0,"currency_code":"GBP","in_stock":false},{"title":"GB \/ NEW \/ INGRAM","offer_id":52487553745169,"sku":"NLS9781119155683","price":0.0,"currency_code":"GBP","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0784\/4072\/6801\/files\/1119155681.jpg?v=1764240272"},{"product_id":"understanding-large-temporal-networks-and-spatial-networks-book-vladimir-batagelj-9780470714522","title":"Understanding Large Temporal Networks and Spatial Networks","description":"A comprehensive, sweeping work by an acclaimed team of authors at the forefront of this hot topic,   Understanding Large Temporal Networks and Spatial Networks explores the different approaches to studying large temporal and spatial networks and links them to computationally sound models of changing structure to detect patterns.","brand":"WoB","offers":[{"title":"- \/ - \/ -","offer_id":50466886582545,"sku":"","price":0.0,"currency_code":"GBP","in_stock":true},{"title":"US \/ GOOD \/ SBYB","offer_id":50466887696657,"sku":"CIN0470714522G","price":0.0,"currency_code":"GBP","in_stock":false}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0784\/4072\/6801\/files\/B01BJ0OY56.jpg?v=1750942712"},{"product_id":"algebraic-analysis-of-social-networks-book-j-antonio-r-ostoic-9781119250388","title":"Algebraic Analysis of Social Networks","description":"Presented in a comprehensive manner, this book provides a comprehensive foundation in algebraic approaches for the analysis of different types of social networks such as multiple, signed, and affiliation networks. The study of such configurations corresponds to the structural analysis within the social sciences, and the methods applied for the analysis are in the areas of abstract algebra, combinatorics, and graph theory.   Current research in social networks has moved toward the examination of more realistic but also more complex social relations by which agents or actors are connected in multiple ways. Addressing this trend, this book offers hands-on training of the algebraic procedures presented along with the computer package multiplex, written by the book’s author specifically to perform analyses of multiple social networks. An introductory section on both complex networks and for R will feature, however the subjects themselves correspond to advanced courses on social network analysis with the specialization on algebraic models and methods.","brand":"WoB","offers":[{"title":"US \/ NEW \/ INGRAM","offer_id":51212018581777,"sku":"NIN9781119250388","price":0.0,"currency_code":"GBP","in_stock":true},{"title":"GB \/ NEW \/ INGRAM","offer_id":52331714969873,"sku":"NLS9781119250388","price":0.0,"currency_code":"GBP","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0784\/4072\/6801\/files\/1119250382.jpg?v=1750791028"},{"product_id":"advances-in-network-clustering-and-blockmodeling-book-patrick-doreian-9781119224709","title":"Advances in Network Clustering and Blockmodeling","description":"Provides an overview of the developments and advances in the field of network clustering and blockmodeling over the last 10 years   This book offers an integrated treatment of network clustering and blockmodeling, covering all of the newest approaches and methods that have been developed over the last decade. Presented in a comprehensive manner, it offers the foundations for understanding network structures and processes, and features a wide variety of new techniques addressing issues that occur during the partitioning of networks across multiple disciplines such as community detection, blockmodeling of valued networks, role assignment, and stochastic blockmodeling.   Written by a team of international experts in the field, Advances in Network Clustering and Blockmodeling offers a plethora of diverse perspectives covering topics such as: bibliometric analyses of the network clustering literature; clustering approaches to networks; label propagation for clustering; and treating missing network data before partitioning. It also examines the partitioning of signed networks, multimode networks, and linked networks. A chapter on structured networks and coarsegrained descriptions is presented, along with another on scientific coauthorship networks. The book finishes with a section covering conclusions and directions for future work. In addition, the editors provide numerous tables, figures, case studies, examples, datasets, and more.     Offers a clear and insightful look at the state of the art in network clustering and blockmodeling Provides an excellent mix of mathematical rigor and practical application in a comprehensive manner Presents a suite of new methods, procedures, algorithms for partitioning networks, as well as new techniques for visualizing matrix arrays Features numerous examples throughout, enabling readers to gain a better understanding of research methods and to conduct their own research effectively Written by leading contributors in the field of spatial networks analysis   Advances in Network Clustering and Blockmodeling is an ideal book for graduate and undergraduate students taking courses on network analysis or working with networks using real data. 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