Using the bootstrap to improve estimation and confidence intervals for regression coefficients selected using backwards variable elimination.

@article{Austin2008UsingTB,
  title={Using the bootstrap to improve estimation and confidence intervals for regression coefficients selected using backwards variable elimination.},
  author={Peter C. Austin},
  journal={Statistics in medicine},
  year={2008},
  volume={27 17},
  pages={3286-300}
}
Applied researchers frequently use automated model selection methods, such as backwards variable elimination, to develop parsimonious regression models. Statisticians have criticized the use of these methods for several reasons, amongst them are the facts that the estimated regression coefficients are biased and that the derived confidence intervals do not have the advertised coverage rates. We developed a method to improve estimation of regression coefficients and confidence intervals which… CONTINUE READING

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