Causal inferences in nonexperimental research

  • 200 Pages
  • 0.44 MB
  • 8778 Downloads
  • English
by
Norton , New York
Social sciences -- Mathematical mo
Statementby Hubert M. Blalock, Jr.
SeriesThe Norton library,, N642
Classifications
LC ClassificationsH61 .B48 1972
The Physical Object
Paginationxii, 200 p.
ID Numbers
Open LibraryOL5284245M
ISBN 100393006425
LC Control Number72002903

Causal Inferences in Nonexperimental Research Paperback – January 1, by Hubert M. Blalock (Author)Cited by: Causal Inferences in Nonexperimental Research (The Norton library) by Hubert M. Blalock () on *FREE* shipping on qualifying offers.

Causal Inferences in Nonexperimental Research (The Norton library) by Hubert M. Blalock ()/5(2). Taking an exploratory rather than a dogmatic approach to the problem, this book pulls together materials bearing on casual inference that are widely scattered in the philosophical, statistical, and social science literature.

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It is written in nonmathematical terms, and it is imaginative and sophisticated from both a theoretical Brand: The University of North Carolina Press. : Causal inferences in nonexperimental research, (The Norton library) () by Blalock, Hubert M and a great selection of similar New, Used and Collectible Books available now at great Range: $ - $ Additional Physical Format: Online version: Blalock, Hubert M.

Causal inferences in nonexperimental research. Chapel Hill, University of North Carolina Press []. DOI: / Corpus ID: Causal Inferences in Nonexperimental Research @inproceedings{BlalockCausalII, title={Causal Inferences in Nonexperimental Research}, author={Hubert M.

Blalock}, year={} }. Causal inferences in Causal inferences in nonexperimental research book research. [Hubert M Blalock] Home. WorldCat Home About WorldCat Help. Search.

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Search for Library Items Search for Lists Search for Book: All Authors / Contributors: Hubert M Blalock. Find more information about: ISBN: OCLC Number: Causal Inference and Modeling H.

() Causal Inferences in Nonexperimental Research, Chapel Hill The book will open the way for including causal analysis in the standard curricula Author: Tuukka Kaidesoja. Since epidemiologi- cal research has established the harm of active smoking based on exclusively observational data, there is consensus that, in order to allow at least some form of causal inference, all of Hill's criteria need to be fulfilled: 13 • Strong association •.

When to Use Nonexperimental Research. As we saw in Chapter 6 "Experimental Research", experimental research is appropriate when the researcher has a specific research question or hypothesis about a causal relationship between two variables—and it is possible, feasible, and ethical to manipulate the independent variable and randomly assign participants to conditions or to orders of.

Similar books and articles. Causal Inferences in Nonexperimental Research. Centore - - Philosophical Studies Children's Causal Inferences From Indirect Evidence: Backwards Blocking and Bayesian Reasoning in Preschoolers.

Alison Gopnik - - Cognitive Science 28 Categories: Bayesian Reasoning, Misc in Philosophy. Types of Nonexperimental Research. Nonexperimental research falls into three broad categories: single-variable research, correlational and quasi-experimental research, and qualitative research.

First, research can be nonexperimental because it focuses on a single variable rather than a statistical relationship between two variables. Robert McGinnis; Causal Inferences in Nonexperimental Research.

By Hubert M. Blalock, Jr. Chapel Hill: The University of North Carolina Press, pp. $5Cited by: 1. Causal Inference from Descriptions of Experimental and Non-Experimental Research: Public Understanding of Correlation-Versus-Causation.

The human tendency to conflate correlation with causation has been lamented by various scientists (Kida, ; Stanovich, ), and vivid examples of it can be found in both the media and peer-reviewed by: 8.

The authors' primary contribution is linking the work on causal inference in diverse fields together, presenting a theoretically coherent view of causal inference that draws extensively on Judea Pearl's work in philosophy and machine learning (see his book Causality: Models, Reasoning and Inference).

The authors successfully illuminate the equations underlying the work of Paul Rosenbaum, Donald /5(12). 'Correctly drawing causal inferences is critical in many important applications.

Congratulations to Professors Imbens and Rubin, who have drawn on their decades of research in this area, along with the work of several others, to produce this impressive book Cited by: Causal Inference 1 (Nonexperimental data) July (12 hours) Bruno Arpino Department of Political and Social Sciences and Research and Expertise Centre for Survey Methodology (RECSM), Pompeu Fabra University Short biography of the instructor Bruno Arpino is an associate professor at the Department of Political and Social.

Causal effects in nonexperimental studies were systematically discussed by Foster () for developmental research and by Lee () for personality research. Hudson and. Find helpful customer reviews and review ratings for Causal Inferences in Nonexperimental Research at Read honest and unbiased product reviews from our users/5.

Electronic books: Additional Physical Format: Print version: Blalock, Hubert M. Causal Inferences in Nonexperimental Research. Chapel Hill: University of North Carolina Press, © Material Type: Document, Internet resource: Document Type: Internet Resource, Computer File: All Authors / Contributors: Hubert M Blalock.

Causal models in the social sciences / by: Blalock, Hubert M., Published: () Causal modeling / by: Asher, Herbert B. Published: () Case studies and causal inference an integrative framework / by: Rohlfing, Ingo.

Published: (). Without "painting" panel data as a cure all for the problems of causal inference in nonexperimental research, the author shows how panel data offer multiple ways of strengthening the causal inference.

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Blalock, Hubert M.Causal inferences in nonexperimental research / by Hubert M. Blalock, Jr University of North Carolina Press Chapel Hill Wikipedia Citation Please see Wikipedia's template documentation for further citation fields that may be required. Pearl/Causal inference in statistics X Y X Y Y X X Yβ X Yβ U U U U x = u y = x + uβ (a) (b) Fig 1.

A simple structural equation model, and its associated diagrams. Unobserved exogenous variables are connected by dashed Size: KB. THE ROLE OF MODEL SELECTION IN CAUSAL INFERENCE FROM NONEXPERIMENTAL DATA JAMES M. ROBINS1 AND SANDER GREENLANDz The article by Starr et al.

(1) in this issue of the Journal provides a valuable starting point to examine the role of model selection when using multivariate models in causal inference.

In their hscussion, Shrr et al. Causal Inference from Observational Data Try explaining to your extended family that you are considered an expert in causal inference.

That’s why, when people ask, I just say that my job is to learn what works for the prevention and treatment of diseases. Kevin D. Hoover, in Philosophy of Economics, 5 Graph-Theoretic Accounts of Causal Structure.

Causal inference using invariance testing is easily overwhelmed by too much happening at once. It works best when one or, at most, a few causal arrows are in question, and it requires (in economic applications, at least) the good fortune to have a few — but not too many — interventions in the.

Berkeley. His research interests include elections, applied and computational statistics, causal inference in observational and experimental studies, voting behavior, public opinion, and the philosophy and history of science. Professor Sekhon received his Ph.D.

in from Cornell. This book is an excellent and relatively non-technical review of causal inference in the social sciences.

The authors condense a huge literature that spans economics, statistics, sociology, /5(15). Steven E. Finkel is the Daniel Wallace Professor of political science at the University of areas of expertise include comparative political behavior, democratization, public opinion, and quantitative methods.

He is the author of Causal Analysis With Panel Data (SAGE, ) as well as numerous articles on political participation, voting behavior, and civic education in new and. Researchers have long struggled to identify causal effects in nonexperimental settings. Many recently proposed strategies assume ignorability of the treatment assignment mechanism and require Author: Jennifer Lynn Hill.

Methods Matter: Improving Causal Inference in Educational and Social Science Research Richard J. Murnane, John B. Willett Oxford University Press, - Psychology - 5/5(1).Explain how causation can be inferred in non-experimental designs The concept of causation is a complex one in the philosophy of science.

Since a full coverage of this topic is well beyond the scope of this text, we focus on two specific topics: (1) the establishment of causation in experiments and (2) the establishment of causation in non.