9781107065079 - Counterfactuals and Causal Inference: Methods and Principles for Social Research Analytical Methods for Social Research by Morgan, Stephen L ; Winship, Christopher (24 results)

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Condition: New. This new edition aims to convince social scientists to take a counterfactual approach to the core questions of their fields. Series: Analytical Methods for Social Research. Num Pages: 524 pages, 64 b/w illus. BIC Classification: JHBC; PBT. Category: (P) Professional & Vocational; (U) Tertiary Education (US: College). Dimension: 263 x 179 x 34. Weight in Grams: 1144. . 2015. 2nd Edition. hardcover. . . . .

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Hardback. Condition: New. In this second edition of Counterfactuals and Causal Inference, completely revised and expanded, the essential features of the counterfactual approach to observational data analysis are presented with examples from the social, demographic, and health sciences. Alternative estimation techniques are first introduced using both the potential outcome model and causal graphs; after which, conditioning techniques, such as matching and regression, are presented from a potential outcomes perspective. For research scenarios in which important determinants of causal exposure are unobserved, alternative techniques, such as instrumental variable estimators, longitudinal methods, and estimation via causal mechanisms, are then presented. The importance of causal effect heterogeneity is stressed throughout the book, and the need for deep causal explanation via mechanisms is discussed.

Condition: New. This new edition aims to convince social scientists to take a counterfactual approach to the core questions of their fields. Series: Analytical Methods for Social Research. Num Pages: 524 pages, 64 b/w illus. BIC Classification: JHBC; PBT. Category: (P) Professional & Vocational; (U) Tertiary Education (US: College). Dimension: 263 x 179 x 34. Weight in Grams: 1144. . 2015. 2nd Edition. hardcover. . . . . Books ship from the US and Ireland.

Condition: New. 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 t.

Hardcover. Condition: Brand New. 2nd edition. 499 pages. 10.25x7.25x1.50 inches. In Stock.

Buch. Condition: Neu. Druck auf Anfrage Neuware - Printed after ordering - In this second edition of Counterfactuals and Causal Inference, completely revised and expanded, the essential features of the counterfactual approach to observational data analysis are presented with examples from the social, demographic, and health sciences. Alternative estimation techniques are first introduced using both the potential outcome model and causal graphs; after which, conditioning techniques, such as matching and regression, are presented from a potential outcomes perspective. For research scenarios in which important determinants of causal exposure are unobserved, alternative techniques, such as instrumental variable estimators, longitudinal methods, and estimation via causal mechanisms, are then presented. The importance of causal effect heterogeneity is stressed throughout the book, and the need for deep causal explanation via mechanisms is discussed.

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Hardback. Condition: New. In this second edition of Counterfactuals and Causal Inference, completely revised and expanded, the essential features of the counterfactual approach to observational data analysis are presented with examples from the social, demographic, and health sciences. Alternative estimation techniques are first introduced using both the potential outcome model and causal graphs; after which, conditioning techniques, such as matching and regression, are presented from a potential outcomes perspective. For research scenarios in which important determinants of causal exposure are unobserved, alternative techniques, such as instrumental variable estimators, longitudinal methods, and estimation via causal mechanisms, are then presented. The importance of causal effect heterogeneity is stressed throughout the book, and the need for deep causal explanation via mechanisms is discussed.

Hardcover. Condition: new. Hardcover. In this second edition of Counterfactuals and Causal Inference, completely revised and expanded, the essential features of the counterfactual approach to observational data analysis are presented with examples from the social, demographic, and health sciences. Alternative estimation techniques are first introduced using both the potential outcome model and causal graphs; after which, conditioning techniques, such as matching and regression, are presented from a potential outcomes perspective. For research scenarios in which important determinants of causal exposure are unobserved, alternative techniques, such as instrumental variable estimators, longitudinal methods, and estimation via causal mechanisms, are then presented. The importance of causal effect heterogeneity is stressed throughout the book, and the need for deep causal explanation via mechanisms is discussed. 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. This item is printed on demand. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.

Hardcover. Condition: Brand New. 2nd edition. 499 pages. 10.25x7.25x1.50 inches. In Stock. This item is printed on demand.

Hardback. Condition: New. This item is printed on demand. New copy - Usually dispatched within 5-9 working days.

Hardcover. Condition: new. Hardcover. In this second edition of Counterfactuals and Causal Inference, completely revised and expanded, the essential features of the counterfactual approach to observational data analysis are presented with examples from the social, demographic, and health sciences. Alternative estimation techniques are first introduced using both the potential outcome model and causal graphs; after which, conditioning techniques, such as matching and regression, are presented from a potential outcomes perspective. For research scenarios in which important determinants of causal exposure are unobserved, alternative techniques, such as instrumental variable estimators, longitudinal methods, and estimation via causal mechanisms, are then presented. The importance of causal effect heterogeneity is stressed throughout the book, and the need for deep causal explanation via mechanisms is discussed. 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. This item is printed on demand. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability.

Condition: New. PRINT ON DEMAND pp. 504.

Buch. Condition: Neu. Counterfactuals and Causal Inference | Stephen L. Morgan (u. a.) | Buch | Gebunden | Englisch | 2015 | Cambridge University Press | EAN 9781107065079 | Verantwortliche Person für die EU: Libri GmbH, Europaallee 1, 36244 Bad Hersfeld, gpsr[at]libri[dot]de | Anbieter: preigu Print on Demand.

Hardcover. Condition: new. Hardcover. In this second edition of Counterfactuals and Causal Inference, completely revised and expanded, the essential features of the counterfactual approach to observational data analysis are presented with examples from the social, demographic, and health sciences. Alternative estimation techniques are first introduced using both the potential outcome model and causal graphs; after which, conditioning techniques, such as matching and regression, are presented from a potential outcomes perspective. For research scenarios in which important determinants of causal exposure are unobserved, alternative techniques, such as instrumental variable estimators, longitudinal methods, and estimation via causal mechanisms, are then presented. The importance of causal effect heterogeneity is stressed throughout the book, and the need for deep causal explanation via mechanisms is discussed. 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. This item is printed on demand. Shipping may be from our Sydney, NSW warehouse or from our UK or US warehouse, depending on stock availability.