The book provides a better understanding of models used in statistical social research.While traditionally understood statistical models relate to data generating processes, this book focuses on analytical models which relate to substantial processes generating social facts. These models are used as a framework for the definition of comparative and dynamic notions of causality.
The book provides a better understanding of models used in statistical social research.While traditionally understood statistical models relate to data generating processes, this book focuses on analytical models which relate to substantial processes generating social facts. These models are used as a framework for the definition of comparative and dynamic notions of causality.
G¿otz Rohwer is professor of methods of social research and statistics at the Ruhr-Universit¿at Bochum (Germany). He has published books and articles on statistical methods, in particular for longitudinal data analysis.
Inhaltsangabe
1. Variables and Relations 1.1 Variables and Distributions 1.2 Relations 2. Notions of Structure 2.1 Statistical Notions of Structure 2.2 Taking Relations into Account 3. Processes and Process Frames 3.1 Historical and Repeatable Processes 3.2 Time Series and Statistical Processes 3.3 Stochastic Process Frames 4. Functional Models 4.1 Deterministic Models 4.2 Models with Stochastic Variables 4.3 Exogenous and Unobserved Variables 5. Functional Causality 5.1 Functional Causes and Conditions 5.2 Ambiguous References to Individuals 5.3 Isolating Functional Causes 6. Models and Statistical Data 6.1 Functional Models and Data 6.2 Experimental and Observational Data 6.3 Interventions and Reference Problems 7. Models with Event Variables 7.1 Situations and Events 7.2 Event Models with Time Axes 7.3 Dynamic Causality 8. Multilevel and Population-level Models 8.1 Conceptual Frameworks 8.2 Models of Statistical Processes 8.3 Functional Causality and Levels
1. Variables and Relations 1.1 Variables and Distributions 1.2 Relations 2. Notions of Structure 2.1 Statistical Notions of Structure 2.2 Taking Relations into Account 3. Processes and Process Frames 3.1 Historical and Repeatable Processes 3.2 Time Series and Statistical Processes 3.3 Stochastic Process Frames 4. Functional Models 4.1 Deterministic Models 4.2 Models with Stochastic Variables 4.3 Exogenous and Unobserved Variables 5. Functional Causality 5.1 Functional Causes and Conditions 5.2 Ambiguous References to Individuals 5.3 Isolating Functional Causes 6. Models and Statistical Data 6.1 Functional Models and Data 6.2 Experimental and Observational Data 6.3 Interventions and Reference Problems 7. Models with Event Variables 7.1 Situations and Events 7.2 Event Models with Time Axes 7.3 Dynamic Causality 8. Multilevel and Population-level Models 8.1 Conceptual Frameworks 8.2 Models of Statistical Processes 8.3 Functional Causality and Levels
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