SOC 6090 - [Causal Inference]

Fall. 2 credits.

Next offered 2014-2015.

S. Morgan.

After a brief review of probability theory and statistical inference, the course introduces techniques and strategies for estimating causal effects from a counterfactual perspective. For problems where potential outcomes exist because they can be specified for well-defined causal states, alternative data analysis techniques will be presented, including matching as stratification, propensity scores as weights in regression analysis, natural experiments as instrumental variable estimators of local average treatment effects, longitudinal data techniques from an interrupted time series perspective, and the front-door criterion for estimating causal effects via the exhaustive modeling of mechanisms. The course is designed primarily for graduate students in sociology and it not suitable for students who have not taken any quantitaive methods classes at the graduate level.

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