Las técnicas de modelización estadística en la investigación educativaminería de datos, modelos de ecuaciones estructurales y modelos jerárquicos lineales

Referencias bibliográficas

• Ato, M., López García, J.J., (1996) Análisis Estadístico Para Datos categóricos, , Madrid, Síntesis
• Bentler, P.M., (2004) EQS Structural Equations Program Manual, , Encino, CA, Multivariate Software, Inc
• Breiman, L., Random forests (2001) Machine Learning, 45 (1), pp. 5-32. , DOI 10.1023/A:1010933404324
• Breiman, L., Friedman, J.H., Olshen, R.A., Stone, C.J., (1984) Classification and Regression Trees, , Belmont, California, Wadsworth
• Browne, M.W., Mels, G., (2005) Path Analysis (RAMONA), en SYSTAT 11 Statistics III [computer Software and Manual] (Richmond, CA, SYSTAT Software Inc.), pp. II1-II61
• Bryk, A.S., Raudenbush, S.W., Congdon, R., (1996) HLM 4 for Windows [Computer software], , Chicago, IL, Scientific Software International, Inc
• Dempster, A.P., Laird, N.M., Rubin, D.B., Maximum likelihood from incomplete data via the EM algorithm (1977) Journal of the Royal Statistical Society, 39, pp. 1-38. , Series B
• Dobson, A., (1990) An Introduction to Generalized Linear Models, , London, Chapman y Hall
• Draper, D., Inference and hierarchical modeling in the social sciences (1995) Journal of Educational and Behavioral Statistics, 20, pp. 115-147
• Estes, W.K., (1991) Statistical Models in Behavioral Research, , Hillsdale, NJ, Elbaum
• Fisher, R.A., (1935) The Design of Experiments, , London, Oliver and Boyd
• Fox, J., Structural equation modeling with the sem package in R (2006) Structural Equation Modeling, 13 (3), pp. 465-486. , DOI 10.1207/s15328007sem1303-7
• Gaviria, J.L., (2000) Cambios en las Técnicas Cuantitativas de Investigación Socio-educativa, p. 3945. , Actas del XII Congreso Nacional y II Iberoamericano de Pedagogía, Madrid
• Gaviria, J.L., Castro, M., (2005) Modelos Jerárquicos Lineales, , Madrid, La Muralla
• Goldstein, H., Multilevel mixed linear models analysis using iterative generalized least squares (1986) Biometrika, 73, pp. 43-56
• Goldstein, H., (2010) Multilevel Statistical Models, , UK, Wiley, 4 th Edition
• Joreskog, K.G., Sörbom, D., (1993) LISREL8: The SIMPLÍS Command Language, , Chicago, IL, Scientific Software Inc
• Jóreskog, K.G., Sórbom, D., (1993) LISREL8; User's Reference Guide, , Chicago, IL, Scientific Software Inc
• Jóreskog, K.G., Sórbom, D., (1993) PREUS2: A Preprocessor for LISREL, , Chicago, IL, Scientific Software Inc
• Jóreskog, K.G., A general method for analysis of covariance structures (1970) Biometrika, 57, pp. 239-251
• Jóreskog, K.G., Statistical analysis of sets of congeneric tests (1971) Psychometrika, 36, pp. 109-133
• Jóreskog, K.G., A general method for estimating a linear structural equation system (1973) Structural Equation Modelling for the Social Sciences, , Goldberger, A. S. y Duncan, O. D. eds., New York, Seminar Press
• Jóreskog, K.G., Statistical models and methods for analysis of longitudinal data (1979) Advances in Factor Analysis and Structural Equation Models, , JÓRESKOG, K. G. y SÓRBOM, D, Cambridge, MA., Abt Books
• Jóreskog, K.G., Sórbom, D., (1999) LISREL8.30: User's Reference Guide, , Chicago, IL, Scientific Software Inc
• Judd, C.M., Mcclelland, G.H., (1989) Data Analysis: A Model Comparison Approach, , San Diego, CA, Hartcourt, Brace and Jovanovich
• Judd, C.M., Mcclelland, G.H., Culhane, S.E., Data analysis: Continuing issues in the everyday analysis of psychological data (1995) Annual Review of Psychology, 46, p. 433465
• Kass, G., An exploratory technique for investigating large quantities of categorical data (1980) Applied Statistics, 29 (2), pp. 119-127
• Kim, S.H., An extension of CART'S pruning algorithm (1991) Program Statistics Research Technical Report No 91-11, , Princeton, New Jersey. Educational Testing Service
• Lindley, D.V., Smith, A.F.M., Bayes estimates for the linear model (1972) Journal of the Royal Statistical Society, 34, p. 141. , Series B
• Lizasoain, L., Joaristi, L., Estudio Diferencial del Rendimiento Académico en Lengua Española de Estudiantes de Educación Secundaria de Baja California (México) (2010) Revista Iberoamericana de Evaluación Educativa, 3 (3), pp. 115-134. , http://www.rinace.net/-riee/numeros/vol3-num3/art6.pdf, Consultado el 15. XII.2010
• Longford, N.T., A fast scoring algorithm for maximum likelihood estimation in unbalanced mixed models with nested random effects (1987) Biometrika, 74, pp. 817-827
• Lunneborg, C.E., (1994) Modeling Experimental and Observational Data, , Belmont, CA, Duxbury Press
• Marsh, H.W., Balla, J.R., Hau, K.-T., An evaluation of incremental fit indices: A clarification of mathematical and empirical properties (1996) Advanced Structural Equation Modeling: Issues and Technique, pp. 315-353. , MARCOULIDES, G. A. y SCHUMACKER, R. E. eds., Hillsdale, NJ, Lawrence Erlbaum Associates
• Muthén, B.O., Muthén, L., (2004) Mplus User's Guide, , Los Angeles, CA, Muthén & Muthén
• Rasbash, J., Goldstein, H., Browne, W., Yang, M., Woodhouse, G., (2000) The MLwiN Command Interface, , Bristol, University of Bristol, Centre for Multilevel Modeling
• Raudenbush, S.W., Bryk, A.S., Congdon, R., (2000) HLM 5 for Windows [Computer Software], , Lincolnwood, IL, Scientific Software International, Inc
• Raudenbush, S.W., Bryk, A.S., Congdon, R., (2004) HLM 6 for Windows [Computer Software], , Lincolnwood, IL, Scientific Software International, Inc
• Raykov, T., Marcoulides, G.A., (2006) A First Course in Structural Equation Modeling, , New Jersey, LEA
• (1989) SAS PROC CALIS User's Guide, , SAS INSTITUTE, Cary, NC, Author
• Smith, A.F.M., Roberts, G.O., Bayesian computation via the Gibbs sampler and related Markov-chain Monte Carlo methods (1993) Journal of the Royal Statistical, 55, pp. 3-23. , Society, Series B
• (1998) User's Guide, , STATISTICA, Tulsa, OK, Statistica Inc
• Strobl, C., Malley, J., Tutz, G., An introduction to recursive partitioning: Rationale, application, and characteristics of classification and regression trees, bagging, and random forests (2009) Psychological Methods, 14 (4), pp. 323-348
• Torgo, L., (2010) Data Mining with R: Learning with Case Studies, , London, Chapman & Hall
• Vandamme, J.-P., Meskens, N., Superby, J.F., Predicting academic performance by data mining methods (2007) Education Economics, 15 (4), p. 405419
• Williams, G., Rattle: A data mining GUI for R (2009) The R Journal, 1 (2), pp. 45-55
• Williams, G., (2011) Data Mining with R and Rattle: The Art of Excavating Data for Knowledge Discovery, , Springer