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Lead Instructor, Missing Data
The Department of Applied Statistics, Social Science, and Humanities at New York University is seeking to hire an instructor for a graduate-level statistics course on Missing Data. The constituency of this course encompasses Masters and PhD students in statistics and the social and health sciences. This seven-week course covers the following topics: (1) simple missing data fixes (for example listwise deletion, available cases, dummy variable methods) and the problems they can create in terms of bias and loss of efficiency, (2) more complicated fixes (e.g. weighting and single imputation) and the assumptions required for valid inference for each, (3) multiple imputation including discussions of the general framework, different models and algorithms and the basic theory. If time allows th
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