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Quantitative analysis of qualitative data

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  • Forrest Young
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    File URL: http://hdl.handle.net/10.1007/BF02293796
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    Bibliographic Info

    Article provided by Springer in its journal Psychometrika.

    Volume (Year): 46 (1981)
    Issue (Month): 4 (December)
    Pages: 357-388

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    Handle: RePEc:spr:psycho:v:46:y:1981:i:4:p:357-388

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    Related research

    Keywords: exploratory data analysis; descriptive data analysis; multivariate data analysis; nonmetric data analysis; alternating least squares; scaling; data theory;

    References

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    1. Richard Sands & Forrest Young, 1980. "Component models for three-way data: An alternating least squares algorithm with optimal scaling features," Psychometrika, Springer, Springer, vol. 45(1), pages 39-67, March.
    2. Forrest Young & Cynthia Null, 1978. "Multidimensional scaling of nominal data: The recovery of metric information with alscal," Psychometrika, Springer, Springer, vol. 43(3), pages 367-379, September.
    3. C. Horan, 1969. "Multidimensional scaling: Combining observations when individuals have different perceptual structures," Psychometrika, Springer, Springer, vol. 34(2), pages 139-165, June.
    4. Yoshio Takane & Forrest Young & Jan Leeuw, 1977. "Nonmetric individual differences multidimensional scaling: An alternating least squares method with optimal scaling features," Psychometrika, Springer, Springer, vol. 42(1), pages 7-67, March.
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    Cited by:
    1. Javier Armando Pineda & Carlos Eduardo Acosta, 2011. "Calidad Del Trabajo: Aproximaciones Teóricas Y Estimación De Un Índice Compuesto," ENSAYOS SOBRE POLÍTICA ECONÓMICA, BANCO DE LA REPÚBLICA - ESPE, BANCO DE LA REPÚBLICA - ESPE.
    2. Groenen, P.J.F. & Nalbantov, G.I. & Bioch, J.C., 2007. "SVM-Maj: a majorization approach to linear support vector machines with different hinge errors," Econometric Institute Research Papers EI 2007-49, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    3. Kuroda, Masahiro & Mori, Yuichi & Iizuka, Masaya & Sakakihara, Michio, 2011. "Acceleration of the alternating least squares algorithm for principal components analysis," Computational Statistics & Data Analysis, Elsevier, Elsevier, vol. 55(1), pages 143-153, January.
    4. Eeke Burg & Jan Leeuw & Renée Verdegaal, 1988. "Homogeneity analysis withk sets of variables: An alternating least squares method with optimal scaling features," Psychometrika, Springer, Springer, vol. 53(2), pages 177-197, June.
    5. Vittadini, Giorgio & Lovaglio, Pietro Giorgio, 2007. "Evaluation of the Dagum-Slottje method to estimate household human capital," Structural Change and Economic Dynamics, Elsevier, Elsevier, vol. 18(2), pages 270-278, June.
    6. Alexandre Gori Maia & José Maria Jardim Da Silveira, 2014. "Farmers’ Preferences For Genetically Modified Corn In Brazil: The Contribution Of Latent Attitudes," Anais do XLI Encontro Nacional de Economia [Proceedings of the 41th Brazilian Economics Meeting], ANPEC - Associação Nacional dos Centros de Pósgraduação em Economia [Brazilian Association of Gra 196, ANPEC - Associação Nacional dos Centros de Pósgraduação em Economia [Brazilian Association of Graduate Programs in Economics].
    7. Shizuhiko Nishisato, 1984. "Forced classification: A simple application of a quantification method," Psychometrika, Springer, Springer, vol. 49(1), pages 25-36, March.
    8. Valderrama, Jose & Pichihua, Juan, 2010. "Propuesta metodológica para la focalización individual de los programas sociales," Working Papers, Banco Central de Reserva del Perú 2010-006, Banco Central de Reserva del Perú.
    9. Heungsun Hwang & Wayne Desarbo & Yoshio Takane, 2007. "Fuzzy Clusterwise Generalized Structured Component Analysis," Psychometrika, Springer, Springer, vol. 72(2), pages 181-198, June.
    10. Valderrama, Jose & Pichihua, Juan, 2011. "Propuesta metodológica para la focalización de los programas sociales," Revista Estudios Económicos, Banco Central de Reserva del Perú, issue 21, pages 65-80.
    11. Kim, Jung Seek & Ratchford, Brian T., 2013. "A Bayesian multivariate probit for ordinal data with semiparametric random-effects," Computational Statistics & Data Analysis, Elsevier, Elsevier, vol. 64(C), pages 192-208.
    12. Giorgio Vittadini & Simona Caterina Minotti, 2005. "A methodology for measuring the relative effectiveness of healthcare services," Working Papers, Università degli Studi di Milano-Bicocca, Dipartimento di Statistica 20050401, Università degli Studi di Milano-Bicocca, Dipartimento di Statistica.
    13. Heungsun Hwang & Yoshio Takane, 2004. "A multivariate reduced-rank growth curve model with unbalanced data," Psychometrika, Springer, Springer, vol. 69(1), pages 65-79, March.
    14. Michel Tenenhaus, 1988. "Canonical analysis of two convex polyhedral cones and applications," Psychometrika, Springer, Springer, vol. 53(4), pages 503-524, December.
    15. Peter Verboon & Ivo Lans, 1994. "Robust canonical discriminant analysis," Psychometrika, Springer, Springer, vol. 59(4), pages 485-507, December.
    16. van Rosmalen, J.M. & Koning, A.J. & Groenen, P.J.F., 2007. "Optimal Scaling of Interaction Effects in Generalized Linear Models," Econometric Institute Research Papers EI 2007-44, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    17. Heungsun Hwang & Yoshio Takane, 2004. "Generalized structured component analysis," Psychometrika, Springer, Springer, vol. 69(1), pages 81-99, March.
    18. Abby Israels, 1984. "Redundancy analysis for qualitative variables," Psychometrika, Springer, Springer, vol. 49(3), pages 331-346, September.
    19. Stef Buuren & Willem Heiser, 1989. "Clusteringn objects intok groups under optimal scaling of variables," Psychometrika, Springer, Springer, vol. 54(4), pages 699-706, September.
    20. Jan Leeuw, 1988. "Multivariate analysis with linearizable regressions," Psychometrika, Springer, Springer, vol. 53(4), pages 437-454, December.
    21. Hansohm, Jürgen, 2004. "Algorithmus und Programm zur Bestimmung der monotonen Kleinst-Quadrate Lösung bei partiellen Präordnungen," Arbeitspapiere zur mathematischen Wirtschaftsforschung 187, Universität Augsburg, Institut für Statistik und Mathematische Wirtschaftstheorie.

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