Beschreibung
InhaltsangabeList of Authors. Acknowledgements. General Introduction; D. Courgeau. 1. Opposition between holism and individualism. 2. How are the two approaches linked? 3. A plurality of aggregation levels and a plurality of time scales. 4. Towards a recomposition and a multilevel analysis. 5. Outline of this volume. 1: Multilevel modelling of educational data; H. Goldstein. 1. Fundamentals: units and levels. 2. The basic multilevel model. 3. Cross-classified models. 4. The multiple membership model. 5. Types of responses. 6. Final thoughts about new insights. 2: From the macro-micro opposition to multilevel analysis in demography; D. Courgeau. 1. Introduction. 2. The aggregate period approach. 3. Cohort analysis. 4. Event history analysis. 5. Contextual and multilevel analysis. 6. Conclusion. 3: Potentialities and limitations of multilevel analysis in public health and epidemiology; A.V. Diez-Roux. 1. Introduction. 2. The presence of multiple levels: conceptual and methodological implications. 3. Multilevel analysis. 4. Multilevel analysis in public health and epidemiology. 5. Challenges raised by the use of multilevel analysis in epidemiology. 6. Limitations and complementary approaches. 4: Exploring small area population structures with census data; M. Tranmer, D. Steel, E. Fieldhouse. 1. Introduction. 2. The concept of multilevel models for geographically based data. 3. Census data availability. 4. Some previous examples of multilevel modelling with census data. 5. Estimating and explaining population structure with census data. 6. Investigating small area variations using SAR with recently added area classifications. 7. Further topics. 8. Conclusion. 5: Organisational levels and time scales in economics; B. Walliser. 1. Introduction. 2. Frozen time. 3. Spread out time. 4. Sequential time. 5. Adaptive time. 6. Individualism versus holism. 7. Economic epistemological positions. 8. Micro and macro-analysis. 9. From theoretical to empirical analysis. 6: Causal analysis, systems analysis, and multilevel analysis: philosophy and epistemology; R. Franck. 1. Introduction. Object of this chapter. 2. The causal principle. 3. Multicausal models. 4. The Stoic principle of causality. 5. Non-causal determinations. 6. The notion of reciprocal action. 7. The nature of levels. 8. Factors and systems. 9. A social philosophy. General Conclusion; D. Courgeau. 1. Experimental versus non-experimental approach. 2. Probability: objectivist, subjectivist and logicist approach. 3. A better definition of levels and a better interconnection between them. 4. Towards a fuller theory. Subject index. Author index.
Inhaltsverzeichnis
List of Authors. Acknowledgements. General Introduction; D. Courgeau. 1. Opposition between holism and individualism. 2. How are the two approaches linked? 3. A plurality of aggregation levels and a plurality of time scales. 4. Towards a recomposition and a multilevel analysis. 5. Outline of this volume. 1: Multilevel modelling of educational data; H. Goldstein. 1. Fundamentals: units and levels. 2. The basic multilevel model. 3. Cross-classified models. 4. The multiple membership model. 5. Types of responses. 6. Final thoughts about new insights. 2: From the macro-micro opposition to multilevel analysis in demography; D. Courgeau. 1. Introduction. 2. The aggregate period approach. 3. Cohort analysis. 4. Event history analysis. 5. Contextual and multilevel analysis. 6. Conclusion. 3: Potentialities and limitations of multilevel analysis in public health and epidemiology; A.V. Diez-Roux. 1. Introduction. 2. The presence of multiple levels: conceptual and methodological implications. 3. Multilevel analysis. 4. Multilevel analysis in public health and epidemiology. 5. Challenges raised by the use of multilevel analysis in epidemiology. 6. Limitations and complementary approaches. 4: Exploring small area population structures with census data; M. Tranmer, D. Steel, E. Fieldhouse. 1. Introduction. 2. The concept of multilevel models for geographically based data. 3. Census data availability. 4. Some previous examples of multilevel modelling with census data. 5. Estimating and explaining population structure with census data. 6. Investigating small area variations using SAR with recently added area classifications. 7. Further topics. 8. Conclusion. 5: Organisational levels and time scales in economics; B. Walliser. 1. Introduction. 2. Frozen time. 3. Spread out time. 4. Sequential time. 5. Adaptive time. 6. Individualism versus holism. 7. Economic epistemological positions. 8. Micro and macro-analysis. 9. From theoretical to empirical analysis. 6: Causal analysis, systems analysis, and multilevel analysis: philosophy and epistemology; R. Franck. 1. Introduction. Object of this chapter. 2. The causal principle. 3. Multicausal models. 4. The Stoic principle of causality. 5. Non-causal determinations. 6. The notion of reciprocal action. 7. The nature of levels. 8. Factors and systems. 9. A social philosophy. General Conclusion; D. Courgeau. 1. Experimental versus non-experimental approach. 2. Probability: objectivist, subjectivist and logicist approach. 3. A better definition of levels and a better interconnection between them. 4. Towards a fuller theory. Subject index. Author index.
Autorenporträt
InhaltsangabeList of Authors. Acknowledgements. General Introduction; D. Courgeau. 1. Opposition between holism and individualism. 2. How are the two approaches linked? 3. A plurality of aggregation levels and a plurality of time scales. 4. Towards a recomposition and a multilevel analysis. 5. Outline of this volume. 1: Multilevel modelling of educational data; H. Goldstein. 1. Fundamentals: units and levels. 2. The basic multilevel model. 3. Cross-classified models. 4. The multiple membership model. 5. Types of responses. 6. Final thoughts about new insights. 2: From the macro-micro opposition to multilevel analysis in demography; D. Courgeau. 1. Introduction. 2. The aggregate period approach. 3. Cohort analysis. 4. Event history analysis. 5. Contextual and multilevel analysis. 6. Conclusion. 3: Potentialities and limitations of multilevel analysis in public health and epidemiology; A.V. Diez-Roux. 1. Introduction. 2. The presence of multiple levels: conceptual and methodological implications. 3. Multilevel analysis. 4. Multilevel analysis in public health and epidemiology. 5. Challenges raised by the use of multilevel analysis in epidemiology. 6. Limitations and complementary approaches. 4: Exploring small area population structures with census data; M. Tranmer, D. Steel, E. Fieldhouse. 1. Introduction. 2. Theconcept of multilevel models for geographically based data. 3. Census data availability. 4. Some previous examples of multilevel modelling with census data. 5. Estimating and explaining population structure with census data. 6. Investigating small area variations using SAR with recently added area classifications. 7. Further topics. 8. Conclusion. 5: Organisational levels and time scales in economics; B. Walliser. 1. Introduction. 2. Frozen time. 3. Spread out time. 4. Sequential time. 5. Adaptive time. 6. Individualism versus holism. 7. Economic epistemological positions. 8. Micro and macro-analysis. 9. From theoretical to empirical analysis. 6: Causal analysis, systems analysis, and multilevel analysis: philosophy and epistemology; R. Franck. 1. Introduction. Object of this chapter. 2. The causal principle. 3. Multicausal models. 4. The Stoic principle of causality. 5. Non-causal determinations. 6. The notion of reciprocal action. 7. The nature of levels. 8. Factors and systems. 9. A social philosophy. General Conclusion; D. Courgeau. 1. Experimental versus non-experimental approach. 2. Probability: objectivist, subjectivist and logicist approach. 3. A better definition of levels and a better interconnection between them. 4. Towards a fuller theory. Subject index. Author index.
