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  • Preface.- Introduction.- 1: Scope of the book and methodology.- 2: Structure of the book.- 3: Philosophical issue in the back of the mind.- 4: Philosophy at the service of social research.- 5: Open problems: causal realism, objectivity, and social ontology.- 1: What do social scientists do?.- Introduction.- 1.1: Different causal claims?.- 1.2: Smoking and lung cancer.- 1.3: Mother's education and child survival.- 1.4: Health and wealth.- 1.5: Farmer's migration.- 1.6: Job satisfaction.- 1.7: Methodological and epistemological morals.- 2: Probabilistic approaches.- Introduction.- 2.1: Philosophical accounts: Good and Suppes.- 2.2: probabilistic theories: traditional criticisms.- 2.3: Brining causal theory to maturity.- 3: Methodology of causal modeling.- Introduction.- 3.1: Methods and assumptions of causal modeling.- 3.1.1: Path models and causal diagrams.- 3.1.2: Covariance structure models.- 3.1.3: Granger-causality.- 3.1.4: Rubin's model.- 3.1.5: Multilevel analysis.- 3.1.6: Contingency tables.- 3.2: Hypothetico-deductive methodology.- 3.3: Difficulties and weaknesses of causal modeling.- 4: Epistemology of causal modeling.- Introduction.- 4.1: The rationale of causality: Measuring variations.- 4.2: Varieties of variations.- 4.3: Wha guarantees the causal interpretation?.- 4.3.1: Associational models.- 4.3.2: Causal models.- 5: Methodological consequences: objective Bayesianism.- Introduction.- 5.1: Probabilistic causal inferences.- 5.2: Interpretations of probability.- 5.3: The case for frequency-driven epistemic probabilities.- 6: Methodological consequences: mechanisms and levels of causation.- Introduction.- 6.1: Mechanisms.- 6.1.1" Modelling mechanisms.- 6.1.2: Mixed mechanisms.- 6.1.3 Explaining through mechanisms.- 6.1.4: Modelling causal mechanisms vs. modeling decision-making processes.- 6.2: Levels of causation.- 6.2.1: Twofold causality.- 6.3: Levels of analysis.- 6.3.1: Types of variables and of fallacies.- 6.3.2: Levels of analysis vs. levels of causation.- 6.3.3: Levels of analysis.- 6.3.4: Levels of analysis and variation in multilevel models.- 7: Supporting the rationale of variations.- Introduction,- 7.1: Variation in mechanist approaches.- 7.2: Variation in counterfactuals.- 7.3: Variation in agency theories.- 7.4: Variation in manipulability theories.- 7.5: Variation in epistemic causality.- 7.6: Variation in single instances: concluding remarks.- 1: Objectives, methodology, and results.- 2: The methodological import of philosophical results.- References.- Index (xsd:string)
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  • 2009 (xsd:gyear)
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  • 2009 (xsd:gyear)
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  • 9781402088162 ()
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  • Causality and causal modelling in social sciences : measuring variations (xsd:string)
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  • Buch (de)
  • Monographie (xsd:string)
  • book (en)
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  • GESIS-BIB (xsd:string)
  • New York: Springer, 2009.- 235 S. (xsd:string)
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