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Causal Models and Intelligent Data Management, Alex Gammerman


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Автор: Alex Gammerman
Название:  Causal Models and Intelligent Data Management
ISBN: 9783642636820
Издательство: Springer
Классификация:




ISBN-10: 3642636829
Обложка/Формат: Paperback
Страницы: 185
Вес: 0.29 кг.
Дата издания: 29.10.2012
Язык: English
Размер: 234 x 156 x 11
Основная тема: Computer Science
Ссылка на Издательство: Link
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Поставляется из: Германии
Описание: The need to electronically store, manipulate and analyze large-scale, high-dimensional data sets requires new computational methods. This book presents new intelligent data management methods and tools, including new results from the field of inference.


Counterfactuals and Causal Inference

Автор: Morgan
Название: Counterfactuals and Causal Inference
ISBN: 1107694167 ISBN-13(EAN): 9781107694163
Издательство: Cambridge Academ
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Цена: 5702.00 р.
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Описание: Cause-and-effect questions are the motivation for most research in the social, demographic, and health sciences. The counterfactual approach to causal analysis represents a unified framework for the prosecution of these questions. This second edition aims to convince more social scientists to take this approach when analyzing these core empirical questions.

Explanation in Causal Inference

Автор: VanderWeele Tyler
Название: Explanation in Causal Inference
ISBN: 0199325871 ISBN-13(EAN): 9780199325870
Издательство: Oxford Academ
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Цена: 18216.00 р.
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Описание: The book provides an accessible but comprehensive overview of methods for mediation and interaction. There has been considerable and rapid methodological development on mediation and moderation/interaction analysis within the causal-inference literature over the last ten years. Much of this
material appears in a variety of specialized journals, and some of the papers are quite technical. There has also been considerable interest in these developments from empirical researchers in the social and biomedical sciences. However, much of the material is not currently in a format that is
accessible to them. The book closes these gaps by providing an accessible, comprehensive, book-length coverage of mediation.

The book begins with a comprehensive introduction to mediation analysis, including chapters on concepts for mediation, regression-based methods, sensitivity analysis, time-to-event outcomes, methods for multiple mediators, methods for time-varying mediation and longitudinal data, and relations
between mediation and other concepts involving intermediates such as surrogates, principal stratification, instrumental variables, and Mendelian randomization. The second part of the book concerns interaction or "moderation," including concepts for interaction, statistical interaction, confounding
and interaction, mechanistic interaction, bias analysis for interaction, interaction in genetic studies, and power and sample-size calculation for interaction. The final part of the book provides comprehensive discussion about the relationships between mediation and interaction and unites these
concepts within a single framework. This final part also provides an introduction to spillover effects or social interaction, concluding with a discussion of social-network analyses.

The book is written to be accessible to anyone with a basic knowledge of statistics. Comprehensive appendices provide more technical details for the interested reader. Applied empirical examples from a variety of fields are given throughout. Software implementation in SAS, Stata, SPSS, and R is
provided. The book should be accessible to students and researchers who have completed a first-year graduate sequence in quantitative methods in one of the social- or biomedical-sciences disciplines. The book will only presuppose familiarity with linear and logistic regression, and could potentially
be used as an advanced undergraduate book as well.

Causal Inference for Statistics, Social, and Biomedical Sciences

Автор: Imbens
Название: Causal Inference for Statistics, Social, and Biomedical Sciences
ISBN: 0521885884 ISBN-13(EAN): 9780521885881
Издательство: Cambridge Academ
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Цена: 8237.00 р.
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Описание: This text presents statistical methods for studying causal effects and discusses how readers can assess such effects in simple randomized experiments.

Counterfactuals and Causal Inference: Methods and Principles for Social Research, 2 ed.

Автор: Stephen L. Morgan, Christopher Winship
Название: Counterfactuals and Causal Inference: Methods and Principles for Social Research, 2 ed.
ISBN: 1107065070 ISBN-13(EAN): 9781107065079
Издательство: Cambridge Academ
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Цена: 13622.00 р.
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Описание: Cause-and-effect questions are the motivation for most research in the social, demographic, and health sciences. The counterfactual approach to causal analysis represents a unified framework for the prosecution of these questions. This second edition aims to convince more social scientists to take this approach when analyzing these core empirical questions.

Causal Nets, Interventionism, and Mechanisms

Автор: Alexander Gebharter
Название: Causal Nets, Interventionism, and Mechanisms
ISBN: 3319499076 ISBN-13(EAN): 9783319499079
Издательство: Springer
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Цена: 12577.00 р.
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Описание: This monograph looks at causal nets from a philosophical point of view. The author shows that one can build a general philosophical theory of causation on the basis of the causal nets framework that can be fruitfully used to shed new light on philosophical issues.

Statistical Causal Inferences and Their Applications in Public Health Research

Автор: He
Название: Statistical Causal Inferences and Their Applications in Public Health Research
ISBN: 3319412574 ISBN-13(EAN): 9783319412573
Издательство: Springer
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Цена: 15372.00 р.
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Описание: This book compiles and presents new developments in statistical causal inference. The accompanying data and computer programs are publicly available so readers may replicate the model development and data analysis presented in each chapter. In this way, methodology is taught so that readers may implement it directly. The book brings together experts engaged in causal inference research to present and discuss recent issues in causal inference methodological development. This is also a timely look at causal inference applied to scenarios that range from clinical trials to mediation and public health research more broadly. In an academic setting, this book will serve as a reference and guide to a course in causal inference at the graduate level (Master's or Doctorate). It is particularly relevant for students pursuing degrees in statistics, biostatistics, and computational biology. Researchers and data analysts in public health and biomedical research will also find this book to be an important reference.

Discovery and Representation of Causal Relationships from a Large Time-Oriented Clinical Database: The RX Project

Автор: R. L. Blum
Название: Discovery and Representation of Causal Relationships from a Large Time-Oriented Clinical Database: The RX Project
ISBN: 3540119620 ISBN-13(EAN): 9783540119623
Издательство: Springer
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Цена: 18167.00 р.
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Описание: As a hospital physician it is impossible to escape the notion that the difficult medical problems one encounters are also being confronted by other` physicians throughout the world. One serious consequence of these characteristics of the medical literature is that patients are largely overtreated.

Causal Models and Intelligent Data Management

Автор: Alex Gammerman
Название: Causal Models and Intelligent Data Management
ISBN: 3540663282 ISBN-13(EAN): 9783540663287
Издательство: Springer
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Цена: 12157.00 р.
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Описание: Presents intelligent data management methods and tools, such as the support vector machine, and results from the field of inference, in particular of causal modeling. In 11 well-structured chapters, leading experts map out the major tendencies and directions of intelligent data analysis.

Semiparametric Structural Equation Models for Causal Discovery

Автор: Shohei Shimizu
Название: Semiparametric Structural Equation Models for Causal Discovery
ISBN: 4431557830 ISBN-13(EAN): 9784431557838
Издательство: Springer
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Цена: 5589.00 р.
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Описание: This is the first book to provide a comprehensive introduction to a new modeling framework known as semiparametric structural equation modeling and its technique, with the fundamental background needed to understand it.

Accounting and Causal Effects

Автор: Douglas A Schroeder
Название: Accounting and Causal Effects
ISBN: 1461426510 ISBN-13(EAN): 9781461426516
Издательство: Springer
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Цена: 30606.00 р.
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Описание: Accounting and Causal Effects builds on econometric foundations to address challenging accounting issues. These include linear, discrete choice, and nonparametric regression models, characterized by microeconomic fundamentals and equilibrium reporting choices.

Real-World Reasoning: Toward Scalable, Uncertain Spatiotemporal,  Contextual and Causal Inference

Автор: Ben Goertzel; Nil Geisweiller; Lucio Coelho; Predr
Название: Real-World Reasoning: Toward Scalable, Uncertain Spatiotemporal, Contextual and Causal Inference
ISBN: 9462390533 ISBN-13(EAN): 9789462390539
Издательство: Springer
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Цена: 13974.00 р.
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Описание: The general problem addressed in this book is a large and important one: how to usefully deal with huge storehouses of complex information about real-world situations.


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