G¨otz Rohwer

Models in Statistical Social Research

• Gebundenes Buch

Produktbeschreibung

Models in Statistical Social Research provides a comprehensive insight of models used in statistical social research based on statistical data and methods. While traditionally understood statistical models relate to data generating processes which presuppose facts, this book focuses on analytical models which relate to substantial processes generating social facts. It formally develops individual-level, population-level, and multilevel versions of such models and uses these models as frameworks for the definition of notions of functional causality. The book further develops a distinction between the representation of states and events, which is then used to formally distinguish between comparative and dynamic notions of causality. It is shown that, due to the involvement of human actors in substantial processes considered in social research, the conceptual framework of randomized experiments is of only limited use. Instead, modelling selection processes should become an explicit task of social research.

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Produktdetails

• Verlag: Routledge
• Seitenzahl: 162
• Erscheinungstermin: 23. November 2009
• Englisch
• Abmessung: 240mm x 161mm x 14mm
• Gewicht: 416g
• ISBN-13: 9780415560559
• ISBN-10: 0415560551
• Artikelnr.: 29020107

Autorenporträt

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