Abstract
The latent structure of psychological data set concerning superstitions is investigated by means of two recent exploratory methods: Grade Correspondence Cluster Analysis (GCCA) and Generalized Association Plots (GAP). The paper compares visualized results in GCCA and GAP. Moreover, it shows what differs both methodologies and what is their intrinsic similarity, according to which the revealed latent structures become equivalent whenever the data set is sufficiently regular. Therefore upon the basis of the real data set, were constructed two types of highly regular simulated data, of the same size and the same multivariate dependence index. These simulated data were then analyzed.
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References
1. Brzozowski, P. (1997) Directiveness Scale of John J. Ray. Warszawa: PTP
2. Chen, C.H. (2002) Generalized Association Plots: Information Visualization via Iteratively Generated Correlation Matrices. Statistica Sinica 12, 7–29
3. Kowalczyk T., Pleszczynska E., Ruland F. (Eds). Grade Models and Methods for Data Analysis, Studies in Fuzziness and Soft Computing No 151. Springer, Berlin-Heidelberg-New York 2004, 1–477
4. Prusik, M. (2001) Symptomaticness of social-political attitudes of Polish society, Unpublished M.s. thesis, Department of Psychology, Warsaw University
5. Wiech, M. (2004) Superstition and its relation to anxiety, authoritarianism and temperamental features, Unpublished M.s. thesis, Department of Psychology, Warsaw University
6. Sosnowski, T., Wiech, M. (2005) Superstition and an attempt to measure it: Questionnaire of Belief Openness KOP20. Roczniki Psychologiczne (in print)
7. Wrzesniewski, K., Sosnowski, T., Matusik, D. (2002) (State-Trait Anger Expression Inventory STAI, Polish adaptation of STAI. Warszawa: PTP
8. Zawadzki, B., Strelau, J. (1997) Formal Characteristic of Behaviour- Temperamental Questionnaire FCZ-KT - Textbook. Warszawa: PTP
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Szczesny, W., Wiech, M. (2006). Visualizing Latent Structures in Grade Correspondence Cluster Analysis and Generalized Association Plots. In: Kłopotek, M.A., Wierzchoń, S.T., Trojanowski, K. (eds) Intelligent Information Processing and Web Mining. Advances in Soft Computing, vol 35. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-33521-8_21
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DOI: https://doi.org/10.1007/3-540-33521-8_21
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-33520-7
Online ISBN: 978-3-540-33521-4
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