Abstract
The preceding chapters have illustrated the validity, the contribution, and the fertility of the multilevel approach applied to different social sciences; but they have also described the main criticisms levelled at the approach as well as the limits encountered when it is applied with excessive rigour.The multilevel approach provides a solution to the problems that occur when working on a single level. It avoids the risks of the ecological and atomistic fallacies by accommodating the effects of characteristics operating at different aggregation levels. By contrast, when we want to examine the set of dynamic, reciprocal, and non-linear relationships that exist inside each level and between levels, the multilevel approach still seems too limited in its present form. We see the need to extend its scope to other analytical strategies introducing new hypotheses. We should investigate and verify whether more complex multilevel models might not offer a fuller approach for the social sciences examined here.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
Bayes, T. R. (1763). An essay towards solving a problem in the doctrine of chances. Philosophical Transactions of the Royal Society of London, 53, 370–418.
Bernoulli, J.I. (1713). Ars conjectandi. Bâle: Impensis Thurnisiorum fratrum.
Cox, R. (1946). Probability, frequency, and reasonable expectation. American Journal of Physics, 14, 1–13.
de Finetti, B. (1974). Theory of probability, 2 vols. London-New York: Wiley and Sons.
Draper, D., Hodges, J. S., Mallows, C. L. and Pregibon, D. (1993). Exchangeability and data analysis. Journal of the Royal Statistical Society A, 156, 9–37.
Fisher, R. A. (1956). Statistical methods and scientific inference. Edinburgh: Oliver and Boyd.
Francis, T. F., Korns, R. F., and Voight, R. B. (1955). An evaluation of the 1954 poliomyelitis vaccine trial. American Journal of Public Health, 45, [suppl.j. l-63.
Franck, R. (Ed.). (2002). The explanatory power of models. Bridging the gap between empirical and theoretical research in the social sciences.,Boston/Dordrecht/London: Kluwer Academic Publishers (Methodos Series, vol. 1).
Gelman, A., Karlin, J. B., Stern, H. S., and Rubin, D. B. (1995). Bayesian data analysis. New York: Chapman and Hall.
Goldstein, H. (1995). Multilevel statistical models. London: Edward Arnold.
Goldstein, H. (1998). Model for reality: new approaches to the understanding of educational processes. Professorial lecture, London: Institute of Education.
Granger, G.-G. (1994). Formes, opérations, objets. Paris: Librairie Philosophique J. Vrin.
Greenland, S. (1998a). Probability logic and probabilistic induction. Epidemiology, 9, 322–332.
Greenland, S. (1998b). Induction versus Popper: substance versus semantics. International Journal of Epidemiology, 27, 543–548.
Greenland, S. (2000). Principles of multilevel modelling. International Journal of Epidemiology, 29, 158–167.
Hoem, J. (1985). Weighting, misclassification, and other issues in the analysis of survey samples of life histories. In Heckman J and Singer B. (Eds.), Longitudinal analysis of labour market data (pp. 259–293 ). Cambridge: Cambridge University Press.
Holland, P. (1986). Statistics and Causal inference (with Comments). Journal of the American Statistical Association, 81, 945–970.
Jaynes, E.T. (1991). How should we use entropy in economics. Unpublished paper. Retrieved October 13, 2001 from: http://www.leibniz.imag.fr/LAPLACE/Jaynes/prob.html.
Jaynes, E. T. (1996). Probability theory: the logic of science. Unpublished book. Retrieved October 13, 2001 from: http://www.leibniz.imag.fr/LAPLACE/Jaynes/prob.html.
Jeffreys, H. (1939). Theory of probability. New York: Clarendon Press.
Jones, K. (1993). Everywhere is nowhere: Multilevel perspectives on the importance of place. The University of Portsmouth Inaugural Lectures.
Kolmogorov, A. (1933). Grundbegriffe der wahrscheinlichkeitsrenung. In Ergebisne der mathematik, vol.2,Berlin.
Laplace, P.S. (1812). Théorie analytique des Probabilités, 2 vols. Paris: Coursier Imprimeur. Lee, P. M. (1997). Bayesian statistics, 2d ed. London: Arnold.
Lelièvre, E., Bonvalet, C. and Bry, X. (1998). Event history analysis of groups. The findings of an on-going research project. ln Courgeau D. (Ed.), Population, An English selection, 10, 11–37.
Lindley, D. V., and Novick, M. R. (1981). The role of exchangeability in inference. The Annals of Statistics, 9, 45–58.
Lindley, D.V., and Smith, A. F. M. (1972). Bayes estimates for the linear model. Journal of the Royal Statistical Society, Series B (Methodological), 34, 1–41.
Lyberg, I. (1983). The effects of sampling and nonresponse on estimates of transition intensities: Some empirical results from the 1981 Swedish fertility survey. Stockholm Research Reports in Demography, n° 14. Stockholm: University of Stockholm.
Matalon, B. (1967). Epistémologie des probabilités. In Piaget J. (Ed.), Logique et connaissance scientifique (pp. 526–553 ), Paris: Gallimard
Polya, G. (1954). Mathematics and plausible reasoning, 2 Vols. Princeton: University Press.
Rosenbaum, P. R. (1984a). The consequence of adjustment for a concomitant variable that has been affected by the treatment. Journal of the Royal Statistical Society A, 147, 656–666
Rosenbaum, P.R. (1984b). From association to causation in observational studies: the role of tests of strongly ignorable treatment assignment. Journal of the American Statistical Association, 79, 41–48.
Rosenbaum, P. R., and Rubin, D. B. (1984). Reducing bias in observational studies using subclassification on the propensity score. Journal of the American Statistical Association, 79, 516–524.
Rubin, D. B. (1978). Bayesian inference for causal effects: the role of randomization. The Annals of Statistics, 6, 34–58.
Schwartz, D. (1989). L’explication en épidémiologie. In Duchéne J., Wunsch G., and Vilquin E. (Eds.), L’explication en sciences sociales. La recherche des causes en démographie (pp. 127–140 ). Louvain-la-Neuve: Editions Ciaco.
Wunsch, G. (1994). L’analyse causale en démographie, in Franck R. (Ed.), Faut-il chercher aux causes une raison ? L’explication causale dans les sciences humaines (pp. 24–40 ). Paris: Librairie Philosophique J. Vrin.
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2003 Springer Science+Business Media Dordrecht
About this chapter
Cite this chapter
Courgeau, D. (2003). General Conclusion. In: Courgeau, D. (eds) Methodology and Epistemology of Multilevel Analysis. Methodos Series, vol 2. Springer, Dordrecht. https://doi.org/10.1007/978-1-4020-4675-9_8
Download citation
DOI: https://doi.org/10.1007/978-1-4020-4675-9_8
Publisher Name: Springer, Dordrecht
Print ISBN: 978-90-481-6365-6
Online ISBN: 978-1-4020-4675-9
eBook Packages: Springer Book Archive