Methods of Evaluation Research II: Probability and Causality

Speakers: Prof. Dr. Rolf Steyer

Summer term 2016, Course, Language: English, Topic: Methods of evaluation research

This lecture is a second course in probability and causality. In the first course the emphasis was on data analysis with EffectLiteR, a computer program for the analysis of conditional and average effects. The probabilistic theory of causal effects was treated but not in much details. In this second course, the focus is on the probabilistic theory of causal effects. It is based on the book "Probability and causality" that is currently in preparation.

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Literature

Causal Effects

Campbell, D. T. & Stanley, J. C. (1963). Experimental and Quasi-Experimental Designs for Research on Teaching. In N. L. Gage (Ed.), Handbook of research on teaching. Chicago: Rand McNally.

West, S. G., Biesanz, J. C. & Pitts, S. C. (2000), Causal inference and generalization in field settings. Experimental and quasi-experimental designs. In H. T. Reis and C. M. Judd (eds.), Handbook of research methods in social and personality psychology. Cambridge University Press.

Steyer, R. (2003). Wahrscheinlichkeit und Regression. Berlin: Springer. (Kapitel 15 - 17)

Steyer, R. (2004). Was wollen und was können wir durch empirische Kausalforschung erfahren? In E. Erdfelder & J. Funke (Hrsg.), Allgemeine Psychologie und deduktivistische Methodologie (pp.127-147). Göttingen: Vandenhoek und Ruprecht.

Steyer, R. (2005). Analyzing Individual and Average Causal Effects via Structural Equation Models. Methodology-European Journal of Research Methods in the Behavioral and Social Sciences, 1, 39-54.

Steyer, R. & Partchev, I. (2006). Manual for EffectLite: A Program for the Uni- and Multivariate Analysis of Unconditional, Conditional and Average Mean Differences Between Groups.

Pohl, S., Steyer, R. & Kraus, K. (2008). Modelling method effects as individual causal effects. Journal of the Royal Statistical Society. Series A, 171, 41--63.

Steyer, R., Partchev, I., Kröhne, U., Nagengast, B., & Fiege, C. (in preparation). Probability and Causality.

Steyer, R., Nagel, W., Partchev, I., & Mayer, A. (in preparation). Probability and Regression.

Preliminary considerations on the definition of the potential confounder sigma-algebra of X with respect to time t_{M} and on the definition of the direct-effect true-outcome variables with respect to time t_{M}