Causal analysis population studies (22 résultats)

Causal Analysis in Population Studies : Concepts, Methods, Applications
Engelhardt, Henriette (EDT); Kohler, Hans-Peter (EDT); Prskawetz, Alexia (EDT)
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Causal Analysis in Population Studies : Concepts, Methods, Applications
Engelhardt, Henriette (EDT); Kohler, Hans-Peter (EDT); Prskawetz, Alexia (EDT)
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Taschenbuch. Etat : Neu. Druck auf Anfrage Neuware - Printed after ordering - The central aim of many studies in population research and demography is to explain cause-effect relationships among variables or events. For decades, population scientists have concentrated their efforts on estimating the 'causes of effects' by applyi…ng standard cross-sectional and dynamic regression techniques, with regression coefficients routinely being understood as estimates of causal effects. The standard approach to infer the 'effects of causes' in natural sciences and in psychology is to conduct randomized experiments. In population studies, experimental designs are generally infeasible.In population studies, most research is based on non-experimental designs (observational or survey designs) and rarely on quasi experiments or natural experiments. Using non-experimental designs to infer causal relationships-i.e. relationships that can ultimately inform policies or interventions-is a complex undertaking. Specifically, treatment effects can be inferred from non-experimental data with a counterfactual approach. In this counterfactual perspective, causal effects are defined as the difference between the potential outcome irrespective of whether or not an individual had received a certain treatment (or experienced a certain cause). The counterfactual approach to estimate effects of causes from quasi-experimental data or from observational studies was first proposed by Rubin in 1974 and further developed by James Heckman and others.This book presents both theoretical contributions and empirical applications of the counterfactual approach to causal inference.

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Buch. Etat : Neu. Druck auf Anfrage Neuware - Printed after ordering - The central aim of many studies in population research and demography is to explain cause-effect relationships among variables or events. For decades, population scientists have concentrated their efforts on estimating the 'causes of effects' by applying stan…dard cross-sectional and dynamic regression techniques, with regression coefficients routinely being understood as estimates of causal effects. The standard approach to infer the 'effects of causes' in natural sciences and in psychology is to conduct randomized experiments. In population studies, experimental designs are generally infeasible.In population studies, most research is based on non-experimental designs (observational or survey designs) and rarely on quasi experiments or natural experiments. Using non-experimental designs to infer causal relationships-i.e. relationships that can ultimately inform policies or interventions-is a complex undertaking. Specifically, treatment effects can be inferred from non-experimental data with a counterfactual approach. In this counterfactual perspective, causal effects are defined as the difference between the potential outcome irrespective of whether or not an individual had received a certain treatment (or experienced a certain cause). The counterfactual approach to estimate effects of causes from quasi-experimental data or from observational studies was first proposed by Rubin in 1974 and further developed by James Heckman and others.This book presents both theoretical contributions and empirical applications of the counterfactual approach to causal inference.

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Taschenbuch. Etat : Neu. Causal Analysis in Population Studies | Concepts, Methods, Applications | Henriette Engelhardt (u. a.) | Taschenbuch | The Springer Series on Demographic Methods and Population Analysis | viii | Englisch | 2010 | Springer | EAN 9789048182329 | Verantwortliche Person für die EU: Springer Verlag GmbH, Tier…gartenstr. 17, 69121 Heidelberg, juergen[dot]hartmann[at]springer[dot]com | Anbieter: preigu.

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Etat : Sehr gut. Zustand: Sehr gut | Sprache: Englisch | Produktart: Bücher | Keine Beschreibung verfügbar.

Causal Analysis in Population Studies : Concepts, Methods, Applications
Engelhardt, Henriette (EDT); Kohler, Hans-Peter (EDT); Prskawetz, Alexia (EDT)
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Causal Analysis in Population Studies : Concepts, Methods, Applications
Engelhardt, Henriette (EDT); Kohler, Hans-Peter (EDT); Prskawetz, Alexia (EDT)
- Couverture rigide
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Buch. Etat : Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -The central aim of many studies in population research and demography is to explain cause-effect relationships among variables or events. For decades, population scientists have concentrated their efforts on estimating the 'causes of effects'…by applying standard cross-sectional and dynamic regression techniques, with regression coefficients routinely being understood as estimates of causal effects. The standard approach to infer the 'effects of causes' in natural sciences and in psychology is to conduct randomized experiments. In population studies, experimental designs are generally infeasible.In population studies, most research is based on non-experimental designs (observational or survey designs) and rarely on quasi experiments or natural experiments. Using non-experimental designs to infer causal relationships-i.e. relationships that can ultimately inform policies or interventions-is a complex undertaking. Specifically, treatment effects can be inferred from non-experimental data with a counterfactual approach. In this counterfactual perspective, causal effects are defined as the difference between the potential outcome irrespective of whether or not an individual had received a certain treatment (or experienced a certain cause). The counterfactual approach to estimate effects of causes from quasi-experimental data or from observational studies was first proposed by Rubin in 1974 and further developed by James Heckman and others.This book presents both theoretical contributions and empirical applications of the counterfactual approach to causal inference. 252 pp. Englisch.

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Vendeur : BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, AllemagneBuchWeltWeit Ludwig Meier e.K.
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Taschenbuch. Etat : Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -The central aim of many studies in population research and demography is to explain cause-effect relationships among variables or events. For decades, population scientists have concentrated their efforts on estimating the 'causes of ef…fects' by applying standard cross-sectional and dynamic regression techniques, with regression coefficients routinely being understood as estimates of causal effects. The standard approach to infer the 'effects of causes' in natural sciences and in psychology is to conduct randomized experiments. In population studies, experimental designs are generally infeasible.In population studies, most research is based on non-experimental designs (observational or survey designs) and rarely on quasi experiments or natural experiments. Using non-experimental designs to infer causal relationships-i.e. relationships that can ultimately inform policies or interventions-is a complex undertaking. Specifically, treatment effects can be inferred from non-experimental data with a counterfactual approach. In this counterfactual perspective, causal effects are defined as the difference between the potential outcome irrespective of whether or not an individual had received a certain treatment (or experienced a certain cause). The counterfactual approach to estimate effects of causes from quasi-experimental data or from observational studies was first proposed by Rubin in 1974 and further developed by James Heckman and others.This book presents both theoretical contributions and empirical applications of the counterfactual approach to causal inference. 260 pp. Englisch.

Causal Analysis in Population Studies
Engelhardt, Henriette|Kohler, Hans-Peter|Fürnkranz-Prskawetz, Alexia
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Etat : New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Estimation of causal relationships based on non-experimental data in population studiesComprehensive discussion of available techniquesContributions by the leading scholars in the fieldThe central aim of many studies in p…opulatio.

Causal Analysis in Population Studies
Engelhardt, Henriette|Kohler, Hans-Peter|Fürnkranz-Prskawetz, Alexia
- Couverture rigide
- impression à la demande
Vendeur : moluna, Greven, Allemagnemoluna
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Etat : New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Estimation of causal relationships based on non-experimental data in population studiesComprehensive discussion of available techniquesContributions by the leading scholars in the fieldThe central aim of many studies in p…opulatio.

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Vendeur : Majestic Books, Hounslow, Royaume-UniMajestic Books
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Etat : New. Print on Demand pp. 260 52:B&W 6.14 x 9.21in or 234 x 156mm (Royal 8vo) Case Laminate on White w/Gloss Lam.

Causal Analysis in Population Studies
Engelhardt Henriette Kohler Hans-Peter F?rnkranz-Prskawetz Alexia
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Vendeur : Biblios, frankfurt am main, HESSE, AllemagneBiblios
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Etat : New. PRINT ON DEMAND pp. 260.

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Taschenbuch. Etat : Neu. This item is printed on demand - Print on Demand Titel. Neuware -The central aim of many studies in population research and demography is to explain cause-effect relationships among variables or events. For decades, population scientists have concentrated their efforts on estimating the 'causes of effect…s' by applying standard cross-sectional and dynamic regression techniques, with regression coefficients routinely being understood as estimates of causal effects. The standard approach to infer the 'effects of causes' in natural sciences and in psychology is to conduct randomized experiments. In population studies, experimental designs are generally infeasible.In population studies, most research is based on non-experimental designs (observational or survey designs) and rarely on quasi experiments or natural experiments. Using non-experimental designs to infer causal relationships-i.e. relationships that can ultimately inform policies or interventions-is a complex undertaking. Specifically, treatment effects can be inferred from non-experimental data with a counterfactual approach. In this counterfactual perspective, causal effects are defined as the difference between the potential outcome irrespective of whether or not an individual had received a certain treatment (or experienced a certain cause). The counterfactual approach to estimate effects of causes from quasi-experimental data or from observational studies was first proposed by Rubin in 1974 and further developed by James Heckman and others.This book presents both theoretical contributions and empirical applications of the counterfactual approach to causal inference.Springer Nature Customer Service Center GmbH, Europaplatz 3, 69115 Heidelberg 260 pp. Englisch.