henriette engelhardt (28 risultati)

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Taschenbuch. Condizione: Neu. Causal Analysis in Population Studies | Concepts, Methods, Applications | Henriette Engelhardt (u. a.) | Taschenbuch | viii | Englisch | 2010 | Springer Netherland | EAN 9789048182329 | Verantwortliche Person für die EU: Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg, juergen[dot]hartmann[at]springer[dot]com | Anbieter: preigu.

Taschenbuch. Condizione: Neu. 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.Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg 260 pp. Englisch.

Taschenbuch. Condizione: 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 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.

Buch. Condizione: 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 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.

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

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Condizione: Sehr Gut. Zustandsbeschreibung: schwarze Filzstiftstriche auf Schnitt. Theoretische und empirische Analysen. 189 Seiten mit einigen Tab., broschiert (Rostocker Beiträge zur Demographie; Band 2/Duncker & Humblot 2002). Statt EUR 62,00. Gewicht: 260 g - Softcover/Taschenbuch.

Hardcover. Condizione: gut. 2011. demographische Entwicklung Anthropologie Demography Demografischer Wandel Bevölkerungssoziologie Sozialwissenschaften Soziologie Demografie BiB Die Schriftenreihe des Bundesinstituts für Bevölkerungsforschung Einführung in die Bevölkerungswissenschaft und Demographie [Gebundene Ausgabe] Henriette Engelhardt (Autor) ISBN-10 3-89913-868-6 / 3899138686 ISBN-13 978-3-89913-868-9 / 9783899138689 In deutscher Sprache. 410 pages. 24,6 x 17,8 x 2,6 cm.

Taschenbuch. Condizione: Neu. Neuware - Im vorliegenden Buch wird von der Theorie, über die Methoden bis hin zu ausgewählten empirischen Fragen die Scheidungsdynamik in Deutschland diskutiert. Mit dem Anstieg der Scheidungsziffern werden sowohl die Dynamik der aggregierten Scheidungsrisiken als auch die Dynamik des individuellen Scheidungsrisikos im Verlauf der ehelichen Beziehung thematisiert.Für den ehedauerabhängigen sichelförmigen Risikoverlauf werden verschiedene Erklärungsansätze diskutiert. In empirischen Analysen untersucht die Autorin zwei Mechanismen, die u. a. für die Dynamik des Scheidungsrisikos verantwortlich gemacht werden: (i) die intergenerationale Transmission des Scheidungsrisikos von der Eltern- auf die Kindergeneration, womit sich - wie bei einem Schneeballeffekt - die Scheidungsrisiken selbst positiv verstärken; (ii) die zunehmende Verbreitung vorehelicher Lebensgemeinschaften, womit sich auf den ersten Blick auch das Scheidungsrisiko zu erhöhen scheint.Anhand der ca. 6000 retrospektiv erhobenen Biographien nicht-lediger Befragter des »Deutschen Familiensurveys« wird gezeigt, daß die intergenerationale Transmission des Scheidungsrisikos für die Dynamik von Ehescheidungen verantwortlich gemacht werden kann, nicht jedoch die steigende Kohabitationsrate. Henriette Engelhardt argumentiert, daß sich der scheidungsfördernde Transmissionseffekt in seiner Dynamik vermutlich abschwächen wird und der de facto scheidungssenkende Kohabitationseffekt offensichtlich nicht in der Lage ist, den säkularen Anstieg der Scheidungsraten zu bremsen.

Taschenbuch. Condizione: Neu. Zur Dynamik von Ehescheidungen. | Theoretische und empirische Analysen. Dissertationsschrift | Henriette Engelhardt | Taschenbuch | 189 S. | Deutsch | 2002 | Duncker & Humblot | EAN 9783428101191 | Verantwortliche Person für die EU: Duncker & Humblot GmbH, Anne Fiedler, Carl-Heinrich-Becker-Weg 9, 12165 Berlin, info[at]duncker-humblot[dot]de | Anbieter: preigu.

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Buch. Condizione: 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.

Taschenbuch. Condizione: 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. 260 pp. Englisch.

Condizione: 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 populatio.

Condizione: 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 populatio.