Introduction to Statistical Decision Theory: Utility Theory and Causal Analysis, Silvia Bacci, Bruno Chiandotto

Автор: Imbens
Название: Causal Inference for Statistics, Social, and Biomedical Sciences
ISBN: 0521885884 ISBN-13(EAN): 9780521885881
Издательство: Cambridge Academ
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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.

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: 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
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.

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: 102480.00 T
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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.

Автор: Markus Frolich, Stefan Sperlich
Название: Impact Evaluation: Treatment Effects and Causal Analysis
ISBN: 1107616069 ISBN-13(EAN): 9781107616066
Издательство: Cambridge Academ
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Цена: 38010.00 T
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Описание: Encompasses the main concepts and approaches of quantitative impact evaluations, used to consider the effectiveness of programmes, policies, projects or interventions. This textbook for economics graduate courses can also serve as a manual for professionals in research institutes, governments, and international organizations.

Автор: James Gareth
Название: An Introduction to Statistical Learning
ISBN: 1461471370 ISBN-13(EAN): 9781461471370
Издательство: Springer
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Цена: 60550.00 T
Наличие на складе: Невозможна поставка.
Описание: This book presents key modeling and prediction techniques, along with relevant applications. Topics include linear regression, classification, resampling methods, shrinkage approaches, tree-based methods, support vector machines, and clustering.

Автор: Alexander Gebharter
Название: Causal Nets, Interventionism, and Mechanisms
ISBN: 3319499076 ISBN-13(EAN): 9783319499079
Издательство: Springer
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Цена: 83850.00 T
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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.

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: 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: 121110.00 T
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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.

Автор: Joseph K. Blitzstein, Jessica Hwang
Название: Introduction to Probability, Second Edition
ISBN: 1138369918 ISBN-13(EAN): 9781138369917
Издательство: Taylor&Francis
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Цена: 74510.00 T
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Описание: Assumes one-semester of calculus. "Stories" make distributions (Normal, Binomial, Poisson that are widely-used in statistics) easier to remember, understand. Many books write down formulas without explaining clearly why these particular distributions are important or how they are all connected.

Автор: Rosenbaum Paul
Название: Observation and Experiment: An Introduction to Causal Inference
ISBN: 0674241630 ISBN-13(EAN): 9780674241633
Издательство: Wiley
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Цена: 25290.00 T
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Описание:

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

Автор: Little
Название: Statistical Analysis with Missing Data, Third Edit ion
ISBN: 0470526793 ISBN-13(EAN): 9780470526798
Издательство: Wiley
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Цена: 84430.00 T
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Описание: Reflecting new application topics, Statistical Analysis with Missing Data offers a thoroughly up-to-date, reorganized survey of current methodology for handling missing data problems. The third edition reviews historical approaches to the subject and describe rigorous yet simple methods for multivariate analysis with missing values.