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Accounting and Causal Effects, Douglas A Schroeder


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Цена: 30606.00р.
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Автор: Douglas A Schroeder
Название:  Accounting and Causal Effects
ISBN: 9781461426516
Издательство: Springer
Классификация:


ISBN-10: 1461426510
Обложка/Формат: Paperback
Страницы: 462
Вес: 0.68 кг.
Дата издания: 2010
Серия: Springer Series in Accounting Scholarship
Язык: English
Иллюстрации: 45 black & white tables, biography
Размер: 234 x 156 x 25
Читательская аудитория: Professional & vocational
Подзаголовок: Econometric challenges
Ссылка на Издательство: Link
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Поставляется из: Германии
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.


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

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.

Causality: Statistical Perspectives and Applications

Автор: Berzuini C
Название: Causality: Statistical Perspectives and Applications
ISBN: 0470665564 ISBN-13(EAN): 9780470665565
Издательство: Wiley
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Цена: 10763.00 р.
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Описание: Providing a thorough treatment on statistical causality, this resource presents a broad collection of contributions from experts in their fields. Methods and their applications are provided with theoretical background and emphasis is given to practice rather than theory, with technical content kept to a minimum.

Evidence, Decision and Causality

Автор: Ahmed
Название: Evidence, Decision and Causality
ISBN: 1316641546 ISBN-13(EAN): 9781316641545
Издательство: Cambridge Academ
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Цена: 5069.00 р.
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Описание: Aimed at philosophers and those with an interest in rational choice. Economic theory, quantum mechanics and voting all seem to illustrate a deep puzzle about the practical role of causality. This book advances the debate, introduces many new examples and assesses the practical relevance of the philosophical discussion.

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.

Causality: A Primer

Автор: Judea Pearl
Название: Causality: A Primer
ISBN: 1119186846 ISBN-13(EAN): 9781119186847
Издательство: Wiley
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Цена: 5061.00 р.
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Описание: Many of the concepts and terminology surrounding modern causal inference can be quite intimidating to the novice. Judea Pearl presents a book ideal for beginners in statistics, providing a comprehensive introduction to the field of causality.

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.


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