3 the observation focus on aggregate or individual behaviours? Will the meth ods used to identify the relationships between the values measured be the same or totally different depending on the level of observation? Can several aggregation levels be used simultaneously? and so on. The social scientist will also need to address the issue of time: Will it be historical time, in which the events studied unfold, or, on the contrary, the time lived by the individual who experiences the events? Will the observation point be a precise moment of that "lived" time, in order to explain the behaviours occurring then by con ditions prevailing immediately beforehand? Or, on the contrary, will the ob servation span an individual's entire life, involving constantly changing conditions? These issues have been present from the very beginning of social science research. We shall address them throughout this volume, and try to find satisfactory solutions. The multilevel approach-which has recently gained ground-tackles the issues from a fresh angle. Within the framework of a single model, it seeks to achieve a synthesis connecting individuals to the society in which they live. For this purpose, it uses intermediate levels, which can vary from one science to another: for example, class and school, in education; the village, the town, and the region, in human geography; the family, the household, and the con tact circle, in demography.
General Introduction.- 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 synthesis.- 5. Outline of this volume.- 1 Multilevel modelling of educational data.- 1. Fundamentals: units and levels.- 2. The basic multilevel model.- 3. Cross-classified models.- 4. The multiple membership model.- 5. Types of response.- 6. Final thoughts about new insights.- 2 From the macro-micro opposition to multilevel analysis in demography.- 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.- 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.- 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 structures 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.- 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.- 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.- 10. Conclusion. Causal analysis, systems analysis, and multilevel analysis.- General Conclusion.- 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.- Author index.
