Автор: B. Sreenivasulu et al. Название: Causality Tests In Econometrics: Choice of Causal Variables ISBN: 3659504041 ISBN-13(EAN): 9783659504044 Издательство: LAP LAMBERT Academic Publishing Рейтинг: Цена: 7472.00 р. Наличие на складе: Нет в наличии.
Описание: In the Present Book Chapter-I is an introductory one.Chapter-II describes the concept and causal relations by econometric models. It presents the different representations such as autoregressive, Moving – average and univariate representation of causality. Chapter-III explore lucidly the various tests for causality, we come across in econometrics. In regression analysis, researchers are interested in testing for the exogenity of variables this testing is closely related to the causality test proposed by Granger, which is explained in detail in this chapter. Chapter-IV gives the conclusions about the present study.The various relevant research articles have been presented under the title BIBLIOGRAPHY.
Описание: This text presents statistical methods for studying causal effects and discusses how readers can assess such effects in simple randomized experiments.
Автор: VanderWeele Tyler Название: Explanation in Causal Inference ISBN: 0199325871 ISBN-13(EAN): 9780199325870 Издательство: Oxford Academ Рейтинг: Цена: 19008.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
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.
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.
A daily glass of wine prolongs life--yet alcohol can cause life-threatening cancer. Some say raising the minimum wage will decrease inequality while others say it increases unemployment. Scientists once confidently claimed that hormone replacement therapy reduced the risk of heart disease but now they equally confidently claim it raises that risk. What should we make of this endless barrage of conflicting claims?
Observation and Experiment is an introduction to causal inference by one of the field's leading scholars. An award-winning professor at Wharton, Paul Rosenbaum explains key concepts and methods through lively examples that make abstract principles accessible. He draws his examples from clinical medicine, economics, public health, epidemiology, clinical psychology, and psychiatry to explain how randomized control trials are conceived and designed, how they differ from observational studies, and what techniques are available to mitigate their bias. "Carefully and precisely written...reflecting superb statistical understanding, all communicated with the skill of a master teacher." --Stephen M. Stigler, author of The Seven Pillars of Statistical Wisdom "An excellent introduction...Well-written and thoughtful...from one of causal inference's noted experts." --Journal of the American Statistical Association "Rosenbaum is a gifted expositor...an outstanding introduction to the topic for anyone who is interested in understanding the basic ideas and approaches to causal inference." --Psychometrika "A very valuable contribution...Highly recommended." --International Statistical Review
Название: Sage handbook of regression analysis and causal inference ISBN: 1446252442 ISBN-13(EAN): 9781446252444 Издательство: Sage Publications Рейтинг: Цена: 21384.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Автор: Pearl Judea Название: Introduction to Causal Inference ISBN: 1507894295 ISBN-13(EAN): 9781507894293 Издательство: Неизвестно Цена: 1723.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Автор: Brumback Babette A. Название: Fundamentals of Causal Inference: With R ISBN: 0367705052 ISBN-13(EAN): 9780367705053 Издательство: Taylor&Francis Рейтинг: Цена: 9645.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Explains and relates different methods of confounding adjustment in terms of potential outcomes and graphical models, including standardization, difference-in-differences estimation, the front-door method, instrumental variables estimation, and propensity score methods.
Автор: Xiong, Momiao (university Of Texas School Of Public Health, Usa) Название: Artificial intelligence and causal inference ISBN: 0367859408 ISBN-13(EAN): 9780367859404 Издательство: Taylor&Francis Рейтинг: Цена: 16078.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Artificial Intelligence and Causal Inference address the recent development of relationships between artificial intelligence (AI) and causal inference. Despite significant progress in AI, a great challenge in AI development we are still facing is to understand mechanism underlying intelligence, including reasoning, planning and imagination.
Автор: Hernan, Miguel A. Название: Causal Inference ISBN: 1420076167 ISBN-13(EAN): 9781420076165 Издательство: Taylor&Francis Рейтинг: Цена: 6430.00 р. Наличие на складе: Нет в наличии.
Описание: This book provides statistics instructors and students with complete classroom material for a one- or two-semester course on applied regression and causal inference. It is built around 52 stories, 52 class-participation activities, 52 hands-on computer demonstrations, and 52 discussion problems that allow instructors and students to explore in a fun way the real-world complexity of the subject. The book fosters an engaging 'flipped classroom' environment with a focus on visualization and understanding. The book provides instructors with frameworks for self-study or for structuring the course, along with tips for maintaining student engagement at all levels, and practice exam questions to help guide learning. Designed to accompany the authors' previous textbook Regression and Other Stories, its modular nature and wealth of material allow this book to be adapted to different courses and texts or be used by learners as a hands-on workbook.
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