Students understand the main features of specific probabilistic inferences in observational studies (e.g. in epidemiology) and can also prepare, in an appropriate manner, causal inferences for research questions which are impossible for experimental study design due to ethical reasons. They know the main study designs in epidemiological studies, surveys and quasi-experimental studies and know the associated weighting and analysis methods. Students gain concrete experience in dealing with one of the popular statistical analysis packages and can independently perform essential data processing steps in the area of observational studies.

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Grundbegriffe bevölkerungsbezogener Maßzahlen für Krankheitsprozesse: Inzidenz, Prävalenz, Remission, Krankheitsdauer, Sterblichkeit. Direkte und indirekte Standardisierungstechniken für populationsbezogene Kennziffern; Risikomaße für potenzielle Krankheitsursachen: relatives und absolutes Risiko, Odds-Ratio, Number needed to treat; Designs zur Bestimmung von Risikomaßen: Fall-Kontroll-Studien, Kohortenstudien; Kontrolltechniken in Beobachtungsstudien; Bestimmung von Gütekriterien für diagnostische Tests (Sensitivität, Spezifität, positiver und negativer prädiktiver Wert, ROC-Analysen); Gesundheits- und Krankheitsindikatoren auf individuellem und Populationsniveau (QALY, DALY);Studien mit ökologischen Daten versus Individualdaten.

Bhopal R (2002) Concepts of Epidemiology: An Integrated Introduction to the Ideas, Theories, Principles and Methods of Epidemiology. Oxford University Press.Rothman KJ (2002) Epidemiology. An Introduction. Oxford: Oxford University PressBerman LF, Kawachi I (Eds.)(2000) Social Epidemiology. Oxford: Oxford University PressShadish WR, Cook TD, Campbell DT (2001) Experimental and Quasi-Experimental Designs for Generalized Causal Inference. Boston: Houghton Mifflin

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