Methodology and Epistemology of Multilevel Analysis: Approaches from Different Social SciencesD. Courgeau Springer Science & Business Media, 2003/07/31 - 235 ページ 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. |
目次
Multilevel modelling of educational data | 25 |
units and levels | 26 |
2 The basic multilevel model | 28 |
3 Crossclassified models | 30 |
4 The multiple membership model | 33 |
5 Types of response | 35 |
6 Final thoughts about new insights | 36 |
From the macromicro opposition to multilevel analysis in demography | 39 |
8 Conclusion | 149 |
Organizational levels and time scaled in economics | 153 |
1 Introduction | 154 |
2 Frozen time | 155 |
3 Spread out time | 157 |
4 Sequential time | 159 |
5 Adaptive time | 160 |
6 Individualism versus holism | 162 |
1 Introduction | 40 |
2 The aggregate period approach | 42 |
3 Cohort analysis | 53 |
4 Event history analysis | 60 |
5 Contextual and multilevel analysis | 70 |
6 Conclusion | 80 |
Potentialities and limitations of multilevel analysis in public health and epidemiology | 89 |
90 | |
conceptual and methodological implications | 93 |
3 Multilevel analysis | 98 |
4 Multilevel analysis in public health and epidemiology | 102 |
5 Challenges raised by the use of multilevel analysis in epidemiology | 104 |
6 Limitations and complementary approaches | 108 |
Exploring small area population structures with census data | 117 |
1 Introduction | 118 |
2 The concept of multilevel models for geographically based data | 119 |
3 Census data availability | 121 |
4 Some previous examples of multilevel modelling with census data | 126 |
5 Estimating and explaining population structures with census data | 128 |
6 Investigating small area variations using SAR with recently added area classifications | 138 |
7 Further topics | 147 |
7 Economic epistemological positions | 164 |
8 Micro and macroanalysis | 166 |
9 From theoretical to empirical analysis | 167 |
Causal analysis systems analysis and multilevel analysis Philosophy and epistemology | 171 |
1 Introduction Objects of this chapter | 172 |
3 Multicausal models | 176 |
4 The Stoic Principle of causality | 180 |
5 Noncausal determination | 183 |
6 The notion of reciprocal action | 184 |
7 The nature of levels | 186 |
8 Factors and systems | 188 |
9 A social philosophy | 190 |
10 Conclusion Causal analysis systems analysis and multilevel analysis | 191 |
GENERAL CONCLUSION | 195 |
Objectivist subjectivist and logicist approach | 199 |
3 A better definition of levels and a better interconnection between them | 204 |
4 Towards a fuller theory | 206 |
Subject Index | 211 |
225 | |
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多く使われている語句
actions agents aggregation levels allow causal causal determination cause census data cohort complex considered context correlation Courgeau covariance cross-classified model defined demographic determination Diez Roux disease ecological fallacy economic effect empirical epidemiology Epistemology estimate event history examine example explain farmers fect fertility Fieldhouse Franck functions geographical given Goldstein Greenland group level variables grouping variables higher level holism hypotheses identified individual characteristics individual level individual level variables inference influence integron interactions large number level data measured methodological methodological holism methodological individualism methods microdata migration mortality multilevel analysis multilevel approach multilevel models multiple nested observed outcomes paradigm parameters Paris period phenomena population structure possible probability problem Public Health random random variables regions regression relation relationship risk Robert Franck sample social sciences society specific statistical sub-populations survey Susser theoretical theory tion Tranmer UNEM unemployment units variance components variation vidual ward level
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