Variable selection in social-environmental data: sparse regression and tree ensemble machine learning approaches

@article{Handorf2020VariableSI,
  title={Variable selection in social-environmental data: sparse regression and tree ensemble machine learning approaches},
  author={Elizabeth A. Handorf and Yinuo Yin and Michael J. Slifker and Shannon M. Lynch},
  journal={BMC Medical Research Methodology},
  year={2020},
  volume={20}
}
Background Social-environmental data obtained from the US Census is an important resource for understanding health disparities, but rarely is the full dataset utilized for analysis. A barrier to incorporating the full data is a lack of solid recommendations for variable selection, with researchers often hand-selecting a few variables. Thus, we evaluated the ability of empirical machine learning approaches to identify social-environmental factors having a true association with a health outcome… 

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