@article{Royston:143012,
      recid = {143012},
      author = {Royston, Patrick and Sauerbrei, Willi},
      title = {Bootstrap assessment of the stability of multivariable  models},
      journal = {Stata Journal},
      address = {2009},
      number = {199-2016-2655},
      pages = {24},
      year = {2009},
      abstract = {Assessing the instability of a multivariable model is  important but is rarely done in practice. Model instability  occurs when selected predictors—and for multivariable  fractional polynomial modeling, selected functions of  continuous predictors—are sensitive to small changes in the  data. Bootstrap analysis is a useful technique for  investigating variations among selected models in samples  drawn at random with replacement. Such samples mimic  datasets that are structurally similar to that under study  and that could plausibly have arisen instead. The bootstrap  inclusion fraction of a candidate variable usefully  indicates the importance of the variable. We describe Stata  tools for stability analysis in the context of the mfp  command for multivariable model building. We offer  practical guidance and illustrate the application of the  tools to a study in prostate cancer.},
      url = {http://ageconsearch.umn.edu/record/143012},
      doi = {https://doi.org/10.22004/ag.econ.143012},
}