ISBN: 9780521885881 - causal inference for statistics, social, and biomedical sciences: an introduction (30 resultados)

Hardcover. Condición: Very Good. 1. It's a well-cared-for item that has seen limited use. The item may show minor signs of wear. All the text is legible, with all pages included. It may have slight markings and/or highlighting.

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Hardcover. Condición: Very Good. 1. It's a well-cared-for item that has seen limited use. The item may show minor signs of wear. All the text is legible, with all pages included. It may have slight markings and/or highlighting.

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hardcover. Condición: New. 1st Edition. Ships in a BOX from Central Missouri! UPS shipping for most packages, (Priority Mail for AK/HI/APO/PO Boxes).

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Hardcover, 625 pages. Condición: Very Good. Eighth Printing. Eighth Printing. Minor bumping to spine and boards. Scuffing to covers. Soiling to text block. Pages are clean and appear to be free of writing and highlighting. Binding is tight.

Condición: Good. This is an ex-library book and may have the usual library/used-book markings inside.This book has hardback covers. In good all round condition. No dust jacket. Please note the Image in this listing is a stock photo and may not match the covers of the actual item,1400grams, ISBN:9780521885881. …

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Hardback. Condición: New. Most questions in social and biomedical sciences are causal in nature: what would happen to individuals, or to groups, if part of their environment were changed? In this groundbreaking text, two world-renowned experts present statistical methods for studying such questions. This book starts with the notion of potential outcomes, each corresponding to the outcome that would be realized if a subject were exposed to a particular treatment or regime. In this approach, causal effects are comparisons of such potential outcomes. The fundamental problem of causal inference is that we can only observe one of the potential outcomes for a particular subject. The authors discuss how randomized experiments allow us to assess causal effects and then turn to observational studies. They lay out the assumptions needed for causal inference and describe the leading analysis methods, including matching, propensity-score methods, and instrumental variables. Many detailed applications are included, with special focus on practical aspects for the empirical researcher. …

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Condición: New. In English.

Condición: New. This text presents statistical methods for studying causal effects and discusses how readers can assess such effects in simple randomized experiments. Num Pages: 644 pages, 18 b/w illus. 97 tables. BIC Classification: PBT. Category: (P) Professional & Vocational. Dimension: 188 x 262 x 36. Weight in Grams: 1292. . 2015. 1st Edition. Hardcover. . . . .…

Hardback. Condición: New. Most questions in social and biomedical sciences are causal in nature: what would happen to individuals, or to groups, if part of their environment were changed? In this groundbreaking text, two world-renowned experts present statistical methods for studying such questions. This book starts with the notion of potential outcomes, each corresponding to the outcome that would be realized if a subject were exposed to a particular treatment or regime. In this approach, causal effects are comparisons of such potential outcomes. The fundamental problem of causal inference is that we can only observe one of the potential outcomes for a particular subject. The authors discuss how randomized experiments allow us to assess causal effects and then turn to observational studies. They lay out the assumptions needed for causal inference and describe the leading analysis methods, including matching, propensity-score methods, and instrumental variables. Many detailed applications are included, with special focus on practical aspects for the empirical researcher. …

Condición: New. pp. 592.

Condición: New. This text presents statistical methods for studying causal effects and discusses how readers can assess such effects in simple randomized experiments. Num Pages: 644 pages, 18 b/w illus. 97 tables. BIC Classification: PBT. Category: (P) Professional & Vocational. Dimension: 188 x 262 x 36. Weight in Grams: 1292. . 2015. 1st Edition. Hardcover. . . . . Books ship from the US and Ireland.…

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Hardcover. Condición: Brand New. 1st edition. 644 pages. 10.50x7.50x1.25 inches. In Stock.

Hardback. Condición: New. Most questions in social and biomedical sciences are causal in nature: what would happen to individuals, or to groups, if part of their environment were changed? In this groundbreaking text, two world-renowned experts present statistical methods for studying such questions. This book starts with the notion of potential outcomes, each corresponding to the outcome that would be realized if a subject were exposed to a particular treatment or regime. In this approach, causal effects are comparisons of such potential outcomes. The fundamental problem of causal inference is that we can only observe one of the potential outcomes for a particular subject. The authors discuss how randomized experiments allow us to assess causal effects and then turn to observational studies. They lay out the assumptions needed for causal inference and describe the leading analysis methods, including matching, propensity-score methods, and instrumental variables. Many detailed applications are included, with special focus on practical aspects for the empirical researcher. …

Buch. Condición: Neu. Druck auf Anfrage Neuware - Printed after ordering - Most questions in social and biomedical sciences are causal in nature: what would happen to individuals, or to groups, if part of their environment were changed In this groundbreaking text, two world-renowned experts present statistical methods for studying such questions. This book starts with the notion of potential outcomes, each corresponding to the outcome that would be realized if a subject were exposed to a particular treatment or regime. In this approach, causal effects are comparisons of such potential outcomes. The fundamental problem of causal inference is that we can only observe one of the potential outcomes for a particular subject. The authors discuss how randomized experiments allow us to assess causal effects and then turn to observational studies. They lay out the assumptions needed for causal inference and describe the leading analysis methods, including matching, propensity-score methods, and instrumental variables. Many detailed applications are included, with special focus on practical aspects for the empirical researcher.…

Hardback. Condición: New. Most questions in social and biomedical sciences are causal in nature: what would happen to individuals, or to groups, if part of their environment were changed? In this groundbreaking text, two world-renowned experts present statistical methods for studying such questions. This book starts with the notion of potential outcomes, each corresponding to the outcome that would be realized if a subject were exposed to a particular treatment or regime. In this approach, causal effects are comparisons of such potential outcomes. The fundamental problem of causal inference is that we can only observe one of the potential outcomes for a particular subject. The authors discuss how randomized experiments allow us to assess causal effects and then turn to observational studies. They lay out the assumptions needed for causal inference and describe the leading analysis methods, including matching, propensity-score methods, and instrumental variables. Many detailed applications are included, with special focus on practical aspects for the empirical researcher. …

Condición: New. Print on Demand pp. 592 18 Illus.

Hardcover. Condición: new. Hardcover. Most questions in social and biomedical sciences are causal in nature: what would happen to individuals, or to groups, if part of their environment were changed? In this groundbreaking text, two world-renowned experts present statistical methods for studying such questions. This book starts with the notion of potential outcomes, each corresponding to the outcome that would be realized if a subject were exposed to a particular treatment or regime. In this approach, causal effects are comparisons of such potential outcomes. The fundamental problem of causal inference is that we can only observe one of the potential outcomes for a particular subject. The authors discuss how randomized experiments allow us to assess causal effects and then turn to observational studies. They lay out the assumptions needed for causal inference and describe the leading analysis methods, including matching, propensity-score methods, and instrumental variables. Many detailed applications are included, with special focus on practical aspects for the empirical researcher. This text presents statistical methods for studying causal effects and discusses how readers can assess such effects in simple randomized experiments. This item is printed on demand. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability.…

Gebunden. Condición: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. This text presents statistical methods for studying causal effects and discusses how readers can assess such effects in simple randomized experiments.Most questions in social and biomedical sciences are causal in nature: what would happen to individ.…

Condición: New. PRINT ON DEMAND pp. 592.

Buch. Condición: Neu. Causal Inference for Statistics, Social, and Biomedical Sciences | Guido W. Imbens (u. a.) | Buch | Geb gebundene Bücher | Englisch | 2019 | Cambridge University Press | EAN 9780521885881 | Verantwortliche Person für die EU: Libri GmbH, Europaallee 1, 36244 Bad Hersfeld, gpsr[at]libri[dot]de | Anbieter: preigu Print on Demand. …