Description: Matched sampling, where the researcher first finds for each exposed unit (e.g., a smoker) a non-exposed unit (e.g., a never-smoker) who looks exactly like the exposed unit except for the exposure, and then compares outcomes (e.g., lung cancer rates) for the matched samples of units, is an intuitive method for inferring the causal effects of exposure versus non-exposure on the colle...
Abstract:The course introduces the foundation in modern statistical thinking regarding causal inference. The first part (I and II of the book) introduces the concepts and discusses classical randomized experiment. The second part (sections III and IV of the book) discusses causal inference using observational data. In Part III we assume that the assignment mechanism is “regular” in a well-de...