Corpus ID: 202539260

Covariate Selection for Generalizing Experimental Results

@article{Egami2019CovariateSF,
  title={Covariate Selection for Generalizing Experimental Results},
  author={Naoki Egami and E. Hartman},
  journal={arXiv: Methodology},
  year={2019}
}
Scientists are interested in generalizing causal effects estimated in an experiment to a target population. However, analysts are often constrained by available covariate information, which has limited applicability of existing approaches that assume rich covariate data from both experimental and population samples. As a concrete context, we focus on a large-scale development program, called the Youth Opportunities Program (YOP), in Uganda. Although more than 40 pre-treatment covariates are… Expand

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