Abstract
A new method based on the Multidimensional Scaling and the Restricted Regression Component Decomposition is proposed in order to obtain solutions for structural models with mixed variables.
This is a preview of subscription content, log in via an institution to check access.
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
Aish, A. M., Jöreskog, K. G. (1990). A panel model for political efficacy and responsiveness: an application of LISREL7 with weighted least squares, Quality and Quantity, 24, 405–426.
Babakus, E., Ferguson, C.E. Jr, Jöreskog K.G. (1987). The sensitivity of confirmatory maximum likelihood factor analysis to violations of measurement scale and distributional assumptions, Journal of Marketing Research, 24, 222–228.
De Leeuw, J., Van Rijckevorsel, J. (1980). Homals & princals, some generalizations of principal components analysis, In E. Diday et al. (Eds.), Data Analysis and Informatics, North-Holland Publishing Company, 231–241.
De Leeuw, J., Young, F.W., Takane Y. (1976). Additive structure in qualitative data: an alternating least squares method with optimal scaling features, Psychometrika, 41, 471–503.
Haagen, K., Vittadini, G. (1991). Regression Component Decomposition in Structural Analysis, Communications in Statistics, 20, 1153–1161.
Haagen, K., Vittadini, G. (1998). Regression Component Decomposition Restricted. Un’alternativa al Lisrel model, Metron, 56, 1–2, in corso di pubblicazione.
Jöreskog, K.G. (1990). New developments in Lisrel: analysis of ordinal variables using polychoric correlations and weighted least squares, Quality and Quantity, 24, 387–404.
Jöreskog, K.G. (1994). On the estimation of polychoric correlations and their asymptotic covariance matrix, Psychometrika, 59, 3, 381–389.
Kiers, H. A. L. (1991). Simple structure in component analysis techniques for mixtures of qualitative and quantitative variables, Psychometrika 56, 2, 197–212.
Keller, W. J., Wansbeek, T. (1983). Multivariate methods for quantitative and qualitative data, Journal of Econometrics, 22, 91–111.
Lee, S.Y, Lam, M. L. (1988). Estimation of polychoric correlation with elliptical latent variables. Journal of statistic Computation and Simulation, 30, 173–188.
Lee, S.Y., Poon, W.Y., Bentler, P.M. (1990). Full maximum likelihood analysis of structural equation models with polytomous variables, Statistics and Probability Letters, 9, 91–97.
Lee, S.Y., Poon, W.Y., Bentler, P.M. (1995). A two-stage estimation of structural equation models with continuous and polytomous variables, British Journal of Mathematical and Statistical Psychology, 48, 339–358.
Muthen, B. (1984). A general structural equation model with dichotomous, ordered categorical, and continuous latent variable indicators, Psychometrika, 49, 1, 115–132.
Quiroga, A.M. (1992). Studies of the Polychoric Correlation and other Correlation Measures for Ordinal Variables, PhD thesis, Uppsala University.
Rigdon, E.E., Ferguson, C.E. Jr. (1991) The performance of the polychoric correlation coefficient and selected fitting functions in confirmatory factor analysis with ordinal data, Journal of Marketing Research, 28, 491–497.
Saito, T., Otsu, T. (1988). A method of optimal scaling for multivariate ordinal data and its extensions, Psychometrika, 53, 1, 5–25.
Van Der Burg, R, De Leeuw, J. (1988). Homogeneity analysis with k sets of variables: an alternating least squares method with optimal scaling features, Psychometrika, 53, 2, 177–197.
Vittadini, G. (1989). Indeterminacy Problems in the LISREL Model, in Multivariate Behavioral Research, Forth Worth (Texas), 24, 4, 397–414.
Wold, H. (1982). Soft Modelling: the basic design and some extensions, in Jöreskog K.G., Wold H., Systems under indirect observation: casuality, structure, prediction, North - Holland, Amsterdam, 2, 1–54.
Young, F.W. (1981). Quantitative analysis of qualitative data, Psychometrika, 46, 357–388.
Young, F.W., De Leeuw, J., Takane, Y. (1976). Regression with qualitative and quantitative variables: an alternating least squares method with optimal scaling features, Psychometrika, 41, 4, 505–529.
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 1999 Springer-Verlag Berlin · Heidelberg
About this paper
Cite this paper
Vittadini, G. (1999). Analysis of Qualitative Variables in Structural Models with Unique Solutions. In: Vichi, M., Opitz, O. (eds) Classification and Data Analysis. Studies in Classification, Data Analysis, and Knowledge Organization. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-60126-2_26
Download citation
DOI: https://doi.org/10.1007/978-3-642-60126-2_26
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-65633-3
Online ISBN: 978-3-642-60126-2
eBook Packages: Springer Book Archive