Multivariate methods: models of dimensionality

Study level: Graduate study programme in psychology
Language: Croatian
Semester: 2nd (summer)
Status: elective
Form of instruction with class hours: 30 hours of lectures and 30 hours of exercises
Prerequisites: none
Student evaluation: Student grades will be based on in-class activity, class participation, and written reports/exam.

Course description

Main content of the subject includes a study of issues regarding the application of selected group of methods for multivariate data analysis particularly aimed at the analysis of interdependencies or the structure of relationships among and between the sets of variables. Among the analyses are factor and cluster analysis, correspondence analysis, multidimensional scaling. The program is regularly limited to 3 methods that have been systematically studied and applied on empirical data. Each topic ends with paper work where students, answering to general questions as well as to those related to actual data sets, have to show that they have mastered the most important issues in application and quantitative interpretation.

Course objectives

The course aims at making students capable of ungoverned work in selection, evaluation of adequacy, and technical implementation of selected methods of multivariate data analysis, as well as in quantitative interpretation of the results obtained by use of these methods.

Required Readings

Fulgosi, A. (1984). Faktorska analiza. Školska knjiga, Zagreb.
Aldenderfer, M. S. i Blashfield, R. K. (1986). Cluster Analysis. Beverly Hills: Sage Publications.
Norusis, M. J. (1993). SPSS for Windows - Professional Statistics. Chicago: SPSS Inc.

Recommended Readings
Grimm, L.G., Yarnold, P.R. (Eds.) (1995). Reading and Understanding Multivariate Statistics. American Psyhological Association., Washington.
Lewis-Beck, M.S. (1994). Factor Analysis and Related Techniques. International Handbooks of Quantitative Applications in the Social Sciences, Vol. 5, London.