Performance Scolaire En Mathématiques Au Benin : Une Analyse Multiniveau A Partir Des Données Du PASEC 2014
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REFERENCES BIBLIOGRAPHIQUES
PASEC (2016). PASEC2014 – Performances du système éducatif béninois : Compétences et facteurs de réussite au primaire. PASEC, CONFEMEN, Dakar.
PASEC (2017). Rapport technique de l’évaluation internationale PASEC2014. PASEC, CONFEMEN, Dakar
Jean-Luc Arrègle 2003/1 Vol. 6 | pages 1 à 28 DOI 10.3917/mana.061.0001
Barcikowski, R. S. 1981 Statistical Power with Group Mean as the Unit of Analysis, Journal of Educational Statistics, 6(3): 267-285.
Bassiri-Gharb, D. 1988 Large and Small Sample Properties of Maximum Likelihood Estimates for the Hierarchical Linear Models, Thèse de Ph.D. non publiée, Educational Psychology and Special Education, Michigan State University.
Bryk, A. S., et S. W. Raudenbush 1992 Hierarchical Linear Models: Applications and Data Analysis Methods, Newbury Park, CA: Sage.
Bryk, A. S., S. W. Raudenbush, et R. Congdon 1999 HLM: Hierarchical Linear and Nonlinear Modeling with the HLM/2L and HLM/3L Programs, Chicago: Scientific Software International.
Burstein, A. 1980a The Analysis of Multi-Level Data in Educational Research and Evaluation, Review of Research in Education, 8:153-223.
Burstein, A. 1980b The Role of Levels of Analysis in the Specification of Educational Effects, in R. Dreeben et J. Thomas (Eds.), Analysis of Educational Productivity: Issues in Microanalysis, Cambridge, MA: Ballinger.
Busing, F. M. T. A. 1993 Distribution Characteristics of Variance Estimates in Two-Level Models, Cahier de recherche, Department of Psychometrics and Research Methodology, Leiden, Pays-Bas.
Dempster, A. P., D. B. Rubin, et R. K. Tsutakawa 1981 Estimation in Covariance Components Models, Journal of the American Statistical Association, 76(374): 341-353.
Granovetter, M. 1985 Economic Action and Social Structure: The Problem of Embeddedness, American Journal of Sociology, 91(3): 481-510.
Goldstein, H. 1987 Multilevels Mixed Linear Models Analysis Using Iterative Generalized Least Squares, Biometrika, 73(1): 43-56.
Goldstein, H. 1995 Multilevel Statistical Models, Londres: Arnold.
Hofmann, D. A. 1997 An Overview of the Logic and Rationale of Hierarchical Linear Models, Journal of Management, 23(6): 723-744.
Hofmann, D. A., et M. Gavin 1998 Centering Decisions in Hierarchical Linear Models: Implications for Research in Organizations, Journal of Management, 24(5): 623-641.
House, R., D. Rousseau, et M. Thomas-Hunt 1995 The Meso Paradigm: A Framework for the Integration of Micro and Macro Organizational Behavior, in L. L. Cummings and B. M. Staw (Eds.), Research in Organizational Behavior, Vol. 17, Greenwich, CT: JAI Press, 71-114.
Hox, J. 1997 Multilevel Modeling: When and Why, in I. Balderjahn, R. Mathar et M. Schrader (Eds.), Classification, Data Analysis and Data Highway: Proceedings of the
st Annual Conference of the Gesellschaft für Klassification, University of Potsdam, March 12-14, New York, NY: Springer-Verlag, 147-154.
James, W., et C. Stein 1961 Estimation with Quadratic Loss, in J. Neyman (Ed.), Proceedings of the Fourth Berkeley Symposium on Mathematical Statistics and Probability, Berkeley, CA: University of California Press, 361-379.
Kelly, R. J., et T. Mathew 1994 Improved Nonnegative Estimation of Variance Components in some Mixed Models with Unbalanced Data, Technometrics, 36(2): 171-181.
Kim, K. S. 1990 Multilevel Data Analysis: A Comparative Examination of Analytical Alternatives (Data Analysis) Comparison of Analytical Alternatives, Thèse de Ph.D. non publiée, Los Angeles, CA: University of California.
Klein, K. J., H. Tosi, et A. Cannella 1999 Multilevel Theory Building: Benefits, Barriers, and New Developments, Academy of Management Review, 24(2): 243-248.
Kreft, I. G., et J. de Leeuw 1998 Introducing Multilevel Modeling, Thousand Oaks, CA: Sage.
Lindley, D. V., et A. F. M. Smith 1972 Bayes Estimates for the Linear Model, Journal of the Royal Statistical Society,
Series B, 34(1): 1-41.
Longford, N. 1987 A Fast Scoring Algorithm for Maximum Likelihood Estimation in Unbalanced Mixed Models with Nested Random Effects, Biometrika, 74(4): 817-827.
Longford, N. 1990 VARCL Software for Variance Component Analysis of Data with Nested Random Effects (Maximum Likelihood), Princeton, NJ: Educational Testing Service.
Mason, W. M., G. M. Wong, et B. Entwistle 1983 Contextual Analysis through the Multilevel Linear Model, in S. Leinhardt (Ed.), Sociological Methodology, San Francisco, CA: Josey-Bass, 72-103.
Morris, C. N. 1983 Parametric Empirical Bayes Inference: Theory and Applications, Journal of the American Statistical Association, 78(381): 47-55.
Rasbash, J., et G. Woodhouse 1995 Mln Command Reference, Londres: University of London, Institute for Education.
Raudenbush, S., A. Bryk, Y. F. Cheong, et R. Congdon 2000 HLM 5: Hierarchical Linear and Nonlinear Modeling, Chicago, IL: Scientific Software International.
Rodriguez, G., et N. Goldman 1995 An Assessment of Estimation Procedures for Multilevel Models with Binary Responses, Journal of the Royal Statistical Society, Series A, 158(1): 73-89.
Rosenberg, B. 1973 Understanding Correlates of Change by Modeling Individual Differences in Growth, Psychometrica, 50: 203-228.
Rowe, K. J. 1999 Accounting for the Hierarchical Structure of Data in Psychosocial Research: An Annotated Example Using Multilevel Structural Equation Modeling, in M. Mok et G. S. Birke (Eds.), Collected Papers on Applications in Multilevel Modeling, Sydney: Macquarie University Press.
Snijders, T. et R. Bosker 1999 Multilevel Analysis: An Introduction to Basic and Advanced Multilevel Modeling,Thousand Oaks, CA: Sage.
Tate, R. L. et Y. Wongbundhit 1983 Random Versus Nonrandom Coefficient Models for Multilevel Analysis,
Journal of Educational Statistics, 8: 103-120.
Tosi, H. 1992 The Environment/Organization/Person Contingency Model: A Meso Approach to the Study of Organizations, Greenwich, CT: JAI Press.
McCulloch, C.E., and Searle, S.R. (2000). Generalized, Linear, and Mixed Models. John Wiley and Sons.
Mortimore, P., Sammons, P., Stoll, L., Lewis, D. and Ecob, R. (1988). School Matters: the Junior Years. Wells, Open Books.
Pinheiro J.C., and Bates, D.M. (2000). Mixed-Effects Models in S and S-PLUS. Springer.
Potthoff, R.F., and Roy, S.N. (1964). “A generalized multivariate analysis of variance model useful especially for growth curve problems.” Biometrika, 51:313-326.
Singer J.D. (1998). “Using SAS PROC MIXED to fix multilevel models, hierarchical models and individual growth models.”Journal of Educational and Behavioral Statistics, 24:323-355.
Verbeke, G., and Molenberghs, G. (2000). Linear Mixed Models for Longitudinal Data. Springer.
Willett, J.B. (1989). “Questions and answers in the measurement of change.” In E.Z. Rothkopf (Ed.) Review of Research in Education, 15:345-422. Washington, DC: American Education Research Association.
Brown, H., & Prescott, R. (2006). Applied mixed models in medicine (2nd ed.). New-York : J. Wiley & Sons. [superbe introduction peu mathématique aux modèles multiniveaux linéaires]
Peugh, J. L., & Enders, C. K. (2005). Using the SPSS Mixed procedure to fit cross sectional and longitudinal multilevel models. Educational and Psychological Measurement, 65(5), 717-741. [article non-mathématique qui refait les analyses multiniveaux de Singer & Willett (2003) avec SPSS].
Raudenbush, S. W., & Bryk, A. S. (2002). Hierarchical Linear Models : Applications
and Data Analysis Methods (2nd ed.). Thousand Oaks, CA : Sage Publications. [livre assez mathématique qui introduit la notation multiniveaux - un classique sur le sujet]
Singer, J. D., & Willett, J. B. (2003). Applied Longitudinal Data Analysis: Modeling Change and Event Occurrence. NYC : Oxford University Press. [les chapitres 1 à 6 sont une superbe introduction non-mathématique aux modèles multiniveaux longitudinaux].
Snijders, T. A. B., & Boske, R. J. (2012). Multilevel Analysis: An Introduction to Basic and Advanced Multilevel Modeling (2nd ed.). Washington, DC : Sage Publications. [livren avancé sur les aspects plus pratiques des modèles multiniveaux].
SPSS. (2005). Linear Mixed-Effects Modeling in SPSS: An Introduction to the MIXED Procedure: SPSS Corporation. [introduction accessible à la procedure SPSS MIXED]
Mohammed Bijou, Narjis Bennouna. Dépenses publiques éducatives et performance scolaire au Maroc. Une analyse multiniveaux à partir des données TIMSS 2015. 2018. hal-01689120
Quelques sites Internet :
https://www.cairn.info/revue-management-2003-1-page-1.htm
www.pasec.confemen.org
http://www.pasec.confemen.org/manuel-des-donnees/
https://hal.archives-ouvertes.fr/hal-01689120
Harvey Goldstein Institute for Education, University of London http://www.ioe.ac.uk/hgpersonal
Teaching Resources and Materials for Social Scientists (site sur la modélisation multiniveaux) http://tramss.data-archive.ac.uk
Centre for Multilevel Group http://multilevel.ioe.ac.uk/index.html
DOI: http://dx.doi.org/10.52155/ijpsat.v50.1.7114
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