Selected Topics in Social Science Statistics

Subject description

Data collection:

  • Survey data collection in social sciences.

  • Secondary sources, administrative data, technical data collection and observational method.

  • The role of new technologies.

  • Data quality and optimization of costs.

  • Processing, archiving and comparative research.

  • Ethical and professional standards.

Statistical analysis:

  • Introductory overview of approaches and models.

  • Multivariate analysis of variables based on nominal, ordinal, interval and ratio scales.

  • Exploratory data analysis and data mining.

  • Missing data treatments:

    • classical approaches (deletion, weighting, single value imputations) and modern approaches (FIML, EM algorithm, multiple imputations).

The subject is taught in programs

Objectives and competences

  • State-of-the-art developments in the field of social science statistics.

  • Comprehensive overview of the field, supplemented by selected lecturers.

  • Qualify students for research and guide their work on the PhD thesis.

Teaching and learning methods

  • Lectures.

  • Preparation of seminar papers.

  • Presentation of research results.

  • Consultations.

Expected study results

Knowledge and understanding:

  • Knowledge of data collection methods used in social sciences and ability to select the appropriate method(s).

  • 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

  • Agresti A. (1990): Categorical Data Analysis. Wiley.

  • Biemer, Lyberg (2003): Introduction to Survey Quality. Wiley.

  • Bishop Y.M.M., Fienberg S.E., Holland P.W. (1975): Discrete Multivariate Analysis: Theory and Practice. MIT Press.

  • Bollen K.A. (1989): Structural Equations with Latent Variables. Wiley, New York.

  • 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.

  • Clogg C.C., Shihadeh E.S. (1994): Statistical Models for Ordinal Variables. Sage.

  • Cox D.R., Wermuth N. (1996): Multivariate Dependencies. Chapman & Hall.

  • Ferligoj A. (1989): Razvrščanje v skupine. Metodološki zvezki, 4, FSPN, Ljubljana.

  • Ferligoj A., Leskošek K., Kogovšek T. (1995): Zanesljivost in veljavnost merjenja. Metodološki zvezki, 11, FDV, Ljubljana.

  • Greenacre M.J. (2007): Correspondence Analysis in Practice (Second Edition). Chapman and Hall/CRC.

  • Greenacre M.J., J. Blasius (ur.) (1994): Correspondence Analysis in the Social Sciences. Academi Press.

  • Groves et al. (ur.) (2004): Survey methodology. Wiley.

  • Hagenaars J.A. (1993): Loglinear Models with Latent Variables. Sage.

  • Härdle, W.,Simar L. (2011): Applied multivariate statistical analysis (2nd ed.). Springer, Berlin.

  • Johnson R.A. in Wichern D.W. (2007): Applied Multivariate Statistical Analysis (6th Edition). Prentice Hall, New Jersey.

  • Kalton, Vehovar (2001): Vzorčenje v anketah. FDV.

  • Little, R. J. & Rubin, D. B. (2002): Statistical analysis with missing data (second edition). Chichester: Wiley.

  • Mardia K.V., Kent J.T. in Billy J.M. (1979): Multivariate Analysis. Academic Press, London.

  • Marsden P.V., Wright J.D. (ur.) (2010): Handbook of Survey Research (Second edition). Emerald, Bingley.

  • Omladič V. (1997): Uporaba linearne algebre v statistiki. Metodološki zvezki, 13, FDV, Ljubljana.

  • Read T.R.C., Cressie N.A.C. (1988): Goodness-of-fit Statistics for Discrete Multivariate Data. Springer.

  • Rudas T. (1997): Odds Ratios in the Analysis of Contingency Tables. Sage.

  • Sieber, J. E. and Tolich, M. B. (2013): Planning Ethically Responsible Research. Sage.

  • Vehovar V. (2012): Nepopolni podatki v anketah. FDV.

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