Subject description
Data collection:
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Survey data collection in social sciences.
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Secondary sources, administrative data, technical data collection and observational method.
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The role of new technologies.
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Data quality and optimization of costs.
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Processing, archiving and comparative research.
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Ethical and professional standards.
Statistical analysis:
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Introductory overview of approaches and models.
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Multivariate analysis of variables based on nominal, ordinal, interval and ratio scales.
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Exploratory data analysis and data mining.
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Missing data treatments:
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classical approaches (deletion, weighting, single value imputations) and modern approaches (FIML, EM algorithm, multiple imputations).
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The subject is taught in programs
Objectives and competences
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State-of-the-art developments in the field of social science statistics.
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Comprehensive overview of the field, supplemented by selected lecturers.
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Qualify students for research and guide their work on the PhD thesis.
Teaching and learning methods
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Lectures.
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Preparation of seminar papers.
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Presentation of research results.
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Consultations.
Expected study results
Knowledge and understanding:
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Knowledge of data collection methods used in social sciences and ability to select the appropriate method(s).
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Knowledge of statistical methods used in social sciences and ability to select the appropriate method(s) based on research questions and type of data.
- Skills to use the literature.
Basic sources and literature
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Agresti A. (1990): Categorical Data Analysis. Wiley.
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Biemer, Lyberg (2003): Introduction to Survey Quality. Wiley.
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Bishop Y.M.M., Fienberg S.E., Holland P.W. (1975): Discrete Multivariate Analysis: Theory and Practice. MIT Press.
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Bollen K.A. (1989): Structural Equations with Latent Variables. Wiley, New York.
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Clogg C.C., Rudas T., Xi L. (1995): A New Index of Structure for the Analysis of Model Misfit, Structure, and Local Structure for Mobility Tables and Other Cross Classifications. V: P. Marsden (ur.) Sociological Methodology. Blackwell, 197-222.
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Clogg C.C., Shihadeh E.S. (1994): Statistical Models for Ordinal Variables. Sage.
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Cox D.R., Wermuth N. (1996): Multivariate Dependencies. Chapman & Hall.
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Ferligoj A. (1989): Razvrščanje v skupine. Metodološki zvezki, 4, FSPN, Ljubljana.
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Ferligoj A., Leskošek K., Kogovšek T. (1995): Zanesljivost in veljavnost merjenja. Metodološki zvezki, 11, FDV, Ljubljana.
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Greenacre M.J. (2007): Correspondence Analysis in Practice (Second Edition). Chapman and Hall/CRC.
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Greenacre M.J., J. Blasius (ur.) (1994): Correspondence Analysis in the Social Sciences. Academi Press.
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Groves et al. (ur.) (2004): Survey methodology. Wiley.
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Hagenaars J.A. (1993): Loglinear Models with Latent Variables. Sage.
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Härdle, W.,Simar L. (2011): Applied multivariate statistical analysis (2nd ed.). Springer, Berlin.
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Johnson R.A. in Wichern D.W. (2007): Applied Multivariate Statistical Analysis (6th Edition). Prentice Hall, New Jersey.
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Kalton, Vehovar (2001): Vzorčenje v anketah. FDV.
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Little, R. J. & Rubin, D. B. (2002): Statistical analysis with missing data (second edition). Chichester: Wiley.
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Mardia K.V., Kent J.T. in Billy J.M. (1979): Multivariate Analysis. Academic Press, London.
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Marsden P.V., Wright J.D. (ur.) (2010): Handbook of Survey Research (Second edition). Emerald, Bingley.
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Omladič V. (1997): Uporaba linearne algebre v statistiki. Metodološki zvezki, 13, FDV, Ljubljana.
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Read T.R.C., Cressie N.A.C. (1988): Goodness-of-fit Statistics for Discrete Multivariate Data. Springer.
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Rudas T. (1997): Odds Ratios in the Analysis of Contingency Tables. Sage.
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Sieber, J. E. and Tolich, M. B. (2013): Planning Ethically Responsible Research. Sage.
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Vehovar V. (2012): Nepopolni podatki v anketah. FDV.
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