Sage handbook of regression analysis and causal inference, 

Автор: Hooshang Nayebi
Название: Advanced Statistics for Testing Assumed Causal Relationships
ISBN: 3030547531 ISBN-13(EAN): 9783030547530
Издательство: Springer
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Цена: 74530.00 T
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Описание: It presents that potential effects of each independent variable on the dependent variable are not limited to direct and indirect effects. The path analysis shows each independent variable has a pure effect on the dependent variable. So, it can be shown the unique contribution of each independent variable to the variation of the dependent variable.

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
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Цена: 49810.00 T
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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.

Автор: Morgan
Название: Counterfactuals and Causal Inference
ISBN: 1107694167 ISBN-13(EAN): 9781107694163
Издательство: Cambridge Academ
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Цена: 38010.00 T
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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.

Автор: VanderWeele Tyler
Название: Explanation in Causal Inference
ISBN: 0199325871 ISBN-13(EAN): 9780199325870
Издательство: Oxford Academ
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Цена: 121440.00 T
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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.

Автор: Bibhas Chakraborty; Erica E.M. Moodie
Название: Statistical Methods for Dynamic Treatment Regimes
ISBN: 1489990305 ISBN-13(EAN): 9781489990303
Издательство: Springer
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Цена: 46570.00 T
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Описание: Statistical Methods for Dynamic Treatment Regimes shares state of the art of statistical methods developed to address questions of estimation and inference for dynamic treatment regimes, a branch of personalized medicine.

Автор: Aki Vehtari, Andrew Gelman
Название: Active Statistics: Stories, Games, Problems, and Hands-on Demonstrations for Applied Regression and Causal Inference
ISBN: 100943621X ISBN-13(EAN): 9781009436212
Издательство: Cambridge Academ
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Цена: 21110.00 T
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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.

Автор: Pearl Judea
Название: Introduction to Causal Inference
ISBN: 1507894295 ISBN-13(EAN): 9781507894293
Издательство: Неизвестно
Цена: 11490.00 T
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Автор: Shadish
Название: Experimental and quasi-experimental designs for generalized causal inference /
ISBN: 0395615569 ISBN-13(EAN): 9780395615560
Издательство: Cengage Learning
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Цена: 73910.00 T
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Описание: This long awaited successor of the original Cook/Campbell Quasi-Experimentation: Design and Analysis Issues for Field Settings represents updates in the field over the last two decades. The book covers four major topics in field experimentation:

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: 90810.00 T
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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.

Автор: Brumback Babette A.
Название: Fundamentals of Causal Inference: With R
ISBN: 0367705052 ISBN-13(EAN): 9780367705053
Издательство: Taylor&Francis
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Цена: 64300.00 T
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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: Burgess, Stephen (mrc Biostatistics Unit, Cambridge, Uk) Thompson, Simon G. (department Of Public Health And Primary Care, University Of Cambridge, Uk
Название: Mendelian randomization
ISBN: 1032019514 ISBN-13(EAN): 9781032019512
Издательство: Taylor&Francis
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Цена: 68390.00 T
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Описание: Mendelian randomization (MR) uses genetic instrumental variables to make inferences about causal effects based on observational data. It, therefore, can be a reliable way of assessing the causal nature of risk factors, such as biomarkers, for a wide range of disease outcomes.

Автор: Hernan, Miguel A.
Название: Causal Inference
ISBN: 1420076167 ISBN-13(EAN): 9781420076165
Издательство: Taylor&Francis
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Цена: 42870.00 T
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