Statistics And Causality

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Causal Inference in Statistics

Author : Judea Pearl
Publisher : John Wiley & Sons
ISBN 13 : 1119186862
Total Pages : 162 pages
Book Rating : 4.1/5 (191 download)

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Book Synopsis Causal Inference in Statistics by : Judea Pearl

Download or read book Causal Inference in Statistics written by Judea Pearl and published by John Wiley & Sons. This book was released on 2016-01-25 with total page 162 pages. Available in PDF, EPUB and Kindle. Book excerpt: CAUSAL INFERENCE IN STATISTICS A Primer Causality is central to the understanding and use of data. Without an understanding of cause–effect relationships, we cannot use data to answer questions as basic as "Does this treatment harm or help patients?" But though hundreds of introductory texts are available on statistical methods of data analysis, until now, no beginner-level book has been written about the exploding arsenal of methods that can tease causal information from data. Causal Inference in Statistics fills that gap. Using simple examples and plain language, the book lays out how to define causal parameters; the assumptions necessary to estimate causal parameters in a variety of situations; how to express those assumptions mathematically; whether those assumptions have testable implications; how to predict the effects of interventions; and how to reason counterfactually. These are the foundational tools that any student of statistics needs to acquire in order to use statistical methods to answer causal questions of interest. This book is accessible to anyone with an interest in interpreting data, from undergraduates, professors, researchers, or to the interested layperson. Examples are drawn from a wide variety of fields, including medicine, public policy, and law; a brief introduction to probability and statistics is provided for the uninitiated; and each chapter comes with study questions to reinforce the readers understanding.

Causality

Author : Judea Pearl
Publisher : Cambridge University Press
ISBN 13 : 052189560X
Total Pages : 487 pages
Book Rating : 4.5/5 (218 download)

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Book Synopsis Causality by : Judea Pearl

Download or read book Causality written by Judea Pearl and published by Cambridge University Press. This book was released on 2009-09-14 with total page 487 pages. Available in PDF, EPUB and Kindle. Book excerpt: Causality offers the first comprehensive coverage of causal analysis in many sciences, including recent advances using graphical methods. Pearl presents a unified account of the probabilistic, manipulative, counterfactual and structural approaches to causation, and devises simple mathematical tools for analyzing the relationships between causal connections, statistical associations, actions and observations. The book will open the way for including causal analysis in the standard curriculum of statistics, artificial intelligence ...

Causal Inference in Statistics, Social, and Biomedical Sciences

Author : Guido W. Imbens
Publisher : Cambridge University Press
ISBN 13 : 0521885884
Total Pages : 647 pages
Book Rating : 4.5/5 (218 download)

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Book Synopsis Causal Inference in Statistics, Social, and Biomedical Sciences by : Guido W. Imbens

Download or read book Causal Inference in Statistics, Social, and Biomedical Sciences written by Guido W. Imbens and published by Cambridge University Press. This book was released on 2015-04-06 with total page 647 pages. Available in PDF, EPUB and Kindle. Book excerpt: This text presents statistical methods for studying causal effects and discusses how readers can assess such effects in simple randomized experiments.

Causality

Author : Carlo Berzuini
Publisher : John Wiley & Sons
ISBN 13 : 1119941733
Total Pages : 387 pages
Book Rating : 4.1/5 (199 download)

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Book Synopsis Causality by : Carlo Berzuini

Download or read book Causality written by Carlo Berzuini and published by John Wiley & Sons. This book was released on 2012-06-04 with total page 387 pages. Available in PDF, EPUB and Kindle. Book excerpt: A state of the art volume on statistical causality Causality: Statistical Perspectives and Applications presents a wide-ranging collection of seminal contributions by renowned experts in the field, providing a thorough treatment of all aspects of statistical causality. It covers the various formalisms in current use, methods for applying them to specific problems, and the special requirements of a range of examples from medicine, biology and economics to political science. This book: Provides a clear account and comparison of formal languages, concepts and models for statistical causality. Addresses examples from medicine, biology, economics and political science to aid the reader's understanding. Is authored by leading experts in their field. Is written in an accessible style. Postgraduates, professional statisticians and researchers in academia and industry will benefit from this book.

The Book of Why

Author : Judea Pearl
Publisher : Basic Books
ISBN 13 : 0465097618
Total Pages : 432 pages
Book Rating : 4.4/5 (65 download)

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Book Synopsis The Book of Why by : Judea Pearl

Download or read book The Book of Why written by Judea Pearl and published by Basic Books. This book was released on 2018-05-15 with total page 432 pages. Available in PDF, EPUB and Kindle. Book excerpt: A Turing Award-winning computer scientist and statistician shows how understanding causality has revolutionized science and will revolutionize artificial intelligence "Correlation is not causation." This mantra, chanted by scientists for more than a century, has led to a virtual prohibition on causal talk. Today, that taboo is dead. The causal revolution, instigated by Judea Pearl and his colleagues, has cut through a century of confusion and established causality -- the study of cause and effect -- on a firm scientific basis. His work explains how we can know easy things, like whether it was rain or a sprinkler that made a sidewalk wet; and how to answer hard questions, like whether a drug cured an illness. Pearl's work enables us to know not just whether one thing causes another: it lets us explore the world that is and the worlds that could have been. It shows us the essence of human thought and key to artificial intelligence. Anyone who wants to understand either needs The Book of Why.

Causal Inference in Statistics

Author : Judea Pearl
Publisher : John Wiley & Sons
ISBN 13 : 1119186854
Total Pages : 160 pages
Book Rating : 4.1/5 (191 download)

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Book Synopsis Causal Inference in Statistics by : Judea Pearl

Download or read book Causal Inference in Statistics written by Judea Pearl and published by John Wiley & Sons. This book was released on 2016-02-03 with total page 160 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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. Examples from classical statistics are presented throughout to demonstrate the need for causality in resolving decision-making dilemmas posed by data. Causal methods are also compared to traditional statistical methods, whilst questions are provided at the end of each section to aid student learning.

The Effect

Author : Nick Huntington-Klein
Publisher : CRC Press
ISBN 13 : 1000509141
Total Pages : 646 pages
Book Rating : 4.0/5 (5 download)

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Book Synopsis The Effect by : Nick Huntington-Klein

Download or read book The Effect written by Nick Huntington-Klein and published by CRC Press. This book was released on 2021-12-20 with total page 646 pages. Available in PDF, EPUB and Kindle. Book excerpt: Extensive code examples in R, Stata, and Python Chapters on overlooked topics in econometrics classes: heterogeneous treatment effects, simulation and power analysis, new cutting-edge methods, and uncomfortable ignored assumptions An easy-to-read conversational tone Up-to-date coverage of methods with fast-moving literatures like difference-in-differences

Statistical Models and Causal Inference

Author : David A. Freedman
Publisher : Cambridge University Press
ISBN 13 : 0521195004
Total Pages : 416 pages
Book Rating : 4.5/5 (211 download)

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Book Synopsis Statistical Models and Causal Inference by : David A. Freedman

Download or read book Statistical Models and Causal Inference written by David A. Freedman and published by Cambridge University Press. This book was released on 2010 with total page 416 pages. Available in PDF, EPUB and Kindle. Book excerpt: David A. Freedman presents a definitive synthesis of his approach to statistical modeling and causal inference in the social sciences.

Elements of Causal Inference

Author : Jonas Peters
Publisher : MIT Press
ISBN 13 : 0262037319
Total Pages : 289 pages
Book Rating : 4.2/5 (62 download)

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Book Synopsis Elements of Causal Inference by : Jonas Peters

Download or read book Elements of Causal Inference written by Jonas Peters and published by MIT Press. This book was released on 2017-11-29 with total page 289 pages. Available in PDF, EPUB and Kindle. Book excerpt: A concise and self-contained introduction to causal inference, increasingly important in data science and machine learning. The mathematization of causality is a relatively recent development, and has become increasingly important in data science and machine learning. This book offers a self-contained and concise introduction to causal models and how to learn them from data. After explaining the need for causal models and discussing some of the principles underlying causal inference, the book teaches readers how to use causal models: how to compute intervention distributions, how to infer causal models from observational and interventional data, and how causal ideas could be exploited for classical machine learning problems. All of these topics are discussed first in terms of two variables and then in the more general multivariate case. The bivariate case turns out to be a particularly hard problem for causal learning because there are no conditional independences as used by classical methods for solving multivariate cases. The authors consider analyzing statistical asymmetries between cause and effect to be highly instructive, and they report on their decade of intensive research into this problem. The book is accessible to readers with a background in machine learning or statistics, and can be used in graduate courses or as a reference for researchers. The text includes code snippets that can be copied and pasted, exercises, and an appendix with a summary of the most important technical concepts.

Fundamentals of Causal Inference

Author : Babette A. Brumback
Publisher : CRC Press
ISBN 13 : 100047030X
Total Pages : 248 pages
Book Rating : 4.0/5 (4 download)

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Book Synopsis Fundamentals of Causal Inference by : Babette A. Brumback

Download or read book Fundamentals of Causal Inference written by Babette A. Brumback and published by CRC Press. This book was released on 2021-11-10 with total page 248 pages. Available in PDF, EPUB and Kindle. Book excerpt: One of the primary motivations for clinical trials and observational studies of humans is to infer cause and effect. Disentangling causation from confounding is of utmost importance. Fundamentals of Causal Inference 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. It also covers effect-measure modification, precision variables, mediation analyses, and time-dependent confounding. Several real data examples, simulation studies, and analyses using R motivate the methods throughout. The book assumes familiarity with basic statistics and probability, regression, and R and is suitable for seniors or graduate students in statistics, biostatistics, and data science as well as PhD students in a wide variety of other disciplines, including epidemiology, pharmacy, the health sciences, education, and the social, economic, and behavioral sciences. Beginning with a brief history and a review of essential elements of probability and statistics, a unique feature of the book is its focus on real and simulated datasets with all binary variables to reduce complex methods down to their fundamentals. Calculus is not required, but a willingness to tackle mathematical notation, difficult concepts, and intricate logical arguments is essential. While many real data examples are included, the book also features the Double What-If Study, based on simulated data with known causal mechanisms, in the belief that the methods are best understood in circumstances where they are known to either succeed or fail. Datasets, R code, and solutions to odd-numbered exercises are available at www.routledge.com.

Causal Inference

Author : Scott Cunningham
Publisher : Yale University Press
ISBN 13 : 0300251688
Total Pages : 585 pages
Book Rating : 4.3/5 (2 download)

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Book Synopsis Causal Inference by : Scott Cunningham

Download or read book Causal Inference written by Scott Cunningham and published by Yale University Press. This book was released on 2021-01-26 with total page 585 pages. Available in PDF, EPUB and Kindle. Book excerpt: An accessible, contemporary introduction to the methods for determining cause and effect in the social sciences "Causation versus correlation has been the basis of arguments--economic and otherwise--since the beginning of time. Causal Inference: The Mixtape uses legit real-world examples that I found genuinely thought-provoking. It's rare that a book prompts readers to expand their outlook; this one did for me."--Marvin Young (Young MC) Causal inference encompasses the tools that allow social scientists to determine what causes what. In a messy world, causal inference is what helps establish the causes and effects of the actions being studied--for example, the impact (or lack thereof) of increases in the minimum wage on employment, the effects of early childhood education on incarceration later in life, or the influence on economic growth of introducing malaria nets in developing regions. Scott Cunningham introduces students and practitioners to the methods necessary to arrive at meaningful answers to the questions of causation, using a range of modeling techniques and coding instructions for both the R and the Stata programming languages.

Causality, Probability, and Time

Author : Samantha Kleinberg
Publisher : Cambridge University Press
ISBN 13 : 1107026482
Total Pages : 269 pages
Book Rating : 4.1/5 (7 download)

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Book Synopsis Causality, Probability, and Time by : Samantha Kleinberg

Download or read book Causality, Probability, and Time written by Samantha Kleinberg and published by Cambridge University Press. This book was released on 2013 with total page 269 pages. Available in PDF, EPUB and Kindle. Book excerpt: Presents a new approach to causal inference and explanation, addressing both the timing and complexity of relationships.

Causal Inference

Author : Miquel A. Hernan
Publisher : CRC Press
ISBN 13 : 9781420076165
Total Pages : 352 pages
Book Rating : 4.0/5 (761 download)

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Book Synopsis Causal Inference by : Miquel A. Hernan

Download or read book Causal Inference written by Miquel A. Hernan and published by CRC Press. This book was released on 2019-07-07 with total page 352 pages. Available in PDF, EPUB and Kindle. Book excerpt: The application of causal inference methods is growing exponentially in fields that deal with observational data. Written by pioneers in the field, this practical book presents an authoritative yet accessible overview of the methods and applications of causal inference. With a wide range of detailed, worked examples using real epidemiologic data as well as software for replicating the analyses, the text provides a thorough introduction to the basics of the theory for non-time-varying treatments and the generalization to complex longitudinal data.

Causality, Probability, and Medicine

Author : Donald Gillies
Publisher : Routledge
ISBN 13 : 1317564286
Total Pages : 261 pages
Book Rating : 4.3/5 (175 download)

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Book Synopsis Causality, Probability, and Medicine by : Donald Gillies

Download or read book Causality, Probability, and Medicine written by Donald Gillies and published by Routledge. This book was released on 2018-08-15 with total page 261 pages. Available in PDF, EPUB and Kindle. Book excerpt: Why is understanding causation so important in philosophy and the sciences? Should causation be defined in terms of probability? Whilst causation plays a major role in theories and concepts of medicine, little attempt has been made to connect causation and probability with medicine itself. Causality, Probability, and Medicine is one of the first books to apply philosophical reasoning about causality to important topics and debates in medicine. Donald Gillies provides a thorough introduction to and assessment of competing theories of causality in philosophy, including action-related theories, causality and mechanisms, and causality and probability. Throughout the book he applies them to important discoveries and theories within medicine, such as germ theory; tuberculosis and cholera; smoking and heart disease; the first ever randomized controlled trial designed to test the treatment of tuberculosis; the growing area of philosophy of evidence-based medicine; and philosophy of epidemiology. This book will be of great interest to students and researchers in philosophy of science and philosophy of medicine, as well as those working in medicine, nursing and related health disciplines where a working knowledge of causality and probability is required.

Unified Methods for Censored Longitudinal Data and Causality

Author : Mark J. van der Laan
Publisher : Springer Science & Business Media
ISBN 13 : 0387217002
Total Pages : 412 pages
Book Rating : 4.3/5 (872 download)

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Book Synopsis Unified Methods for Censored Longitudinal Data and Causality by : Mark J. van der Laan

Download or read book Unified Methods for Censored Longitudinal Data and Causality written by Mark J. van der Laan and published by Springer Science & Business Media. This book was released on 2012-11-12 with total page 412 pages. Available in PDF, EPUB and Kindle. Book excerpt: A fundamental statistical framework for the analysis of complex longitudinal data is provided in this book. It provides the first comprehensive description of optimal estimation techniques based on time-dependent data structures. The techniques go beyond standard statistical approaches and can be used to teach masters and Ph.D. students. The text is ideally suitable for researchers in statistics with a strong interest in the analysis of complex longitudinal data.

Causation, Prediction, and Search

Author : Peter Spirtes
Publisher : Springer Science & Business Media
ISBN 13 : 1461227488
Total Pages : 551 pages
Book Rating : 4.4/5 (612 download)

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Book Synopsis Causation, Prediction, and Search by : Peter Spirtes

Download or read book Causation, Prediction, and Search written by Peter Spirtes and published by Springer Science & Business Media. This book was released on 2012-12-06 with total page 551 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book is intended for anyone, regardless of discipline, who is interested in the use of statistical methods to help obtain scientific explanations or to predict the outcomes of actions, experiments or policies. Much of G. Udny Yule's work illustrates a vision of statistics whose goal is to investigate when and how causal influences may be reliably inferred, and their comparative strengths estimated, from statistical samples. Yule's enterprise has been largely replaced by Ronald Fisher's conception, in which there is a fundamental cleavage between experimental and non experimental inquiry, and statistics is largely unable to aid in causal inference without randomized experimental trials. Every now and then members of the statistical community express misgivings about this turn of events, and, in our view, rightly so. Our work represents a return to something like Yule's conception of the enterprise of theoretical statistics and its potential practical benefits. If intellectual history in the 20th century had gone otherwise, there might have been a discipline to which our work belongs. As it happens, there is not. We develop material that belongs to statistics, to computer science, and to philosophy; the combination may not be entirely satisfactory for specialists in any of these subjects. We hope it is nonetheless satisfactory for its purpose.

Advanced Statistics for Testing Assumed Causal Relationships

Author : Hooshang Nayebi
Publisher : Springer Nature
ISBN 13 : 303054754X
Total Pages : 125 pages
Book Rating : 4.0/5 (35 download)

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Book Synopsis Advanced Statistics for Testing Assumed Causal Relationships by : Hooshang Nayebi

Download or read book Advanced Statistics for Testing Assumed Causal Relationships written by Hooshang Nayebi and published by Springer Nature. This book was released on 2020-08-15 with total page 125 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book concentrates on linear regression, path analysis and logistic regressions, the most used statistical techniques for the test of causal relationships. Its emphasis is on the conceptions and applications of the techniques by using simple examples without requesting any mathematical knowledge. It shows multiple regression analysis accurately reconstructs the causal relationships between phenomena. So, it can be used to test the hypotheses about causal relationships between variables. 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. It is an advanced statistical text for the graduate students in social and behavior sciences. It also serves as a reference for professionals and researchers.