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Research Design: Causality in Quantitative Research Designs

Research Design: Causality in Quantitative Research Designs. Armen Hakhverdian a.hakhverdian@uva.nl. Course outline. Topics Introduction Potential Outcomes Framework Randomized Experiments (classical, field, survey, natural) Regression and causality; interaction effects

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Research Design: Causality in Quantitative Research Designs

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  1. Research Design: Causality in Quantitative Research Designs Armen Hakhverdian a.hakhverdian@uva.nl

  2. Course outline • Topics • Introduction • Potential Outcomes Framework • Randomized Experiments (classical, field, survey, natural) • Regression and causality; interaction effects • Hierarchical models; time-series analysis • Mixed methods • Quasi-experimental designs

  3. Course outline • Teaching format: • Lectures on Mondays • Explanation of weekly readings • Discussion seminars on Fridays • Discussion of assignments • Applications of methods to ‘substantive’ social science topics • Previous knowledge • Introduction to statistics up to regression analysis • Assessment • Two papers • Deadline forfinal paper tobe set in class

  4. Life beyond RD: Causality? • RMSS • Measurementmodelsand data theory (Gijs Schumacher) • Advanced multivariate modelling (Stephanie Steinmetz) • Fixedand random effects (Thomas Leopold) • Electives (selection) • Advanced Network Analysis • Analysis of Tekst & Discourse • Survey Design • Big Data • Experimentation • Replication • Geographical Information Systems (GIS)

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