Assessing model mimicry using the parametric bootstrap

@inproceedings{Wagenmakers2004AssessingMM,
  title={Assessing model mimicry using the parametric bootstrap},
  author={Eric-Jan Wagenmakers and Roger Ratcliff and Pablo G{\'o}mez and Geoffrey J. Iversonc},
  year={2004}
}
We present a general sampling procedure to quantify model mimicry, defined as the ability of a model to account for data generated by a competing model. This sampling procedure, called the parametric bootstrap cross-fitting method (PBCM; cf. Williams (J. R. Statist. Soc. B 32 (1970) 350; Biometrics 26 (1970) 23)), generates distributions of differences in goodness-of-fit expected under each of the competing models. In the data informed version of the PBCM, the generating models have specific… CONTINUE READING

Citations

Publications citing this paper.
Showing 1-10 of 66 extracted citations

The Self-Organization of a Spoken Word

Front. Psychology • 2012
View 1 Excerpt
Highly Influenced

Provenance of correlations in psychological data.

Psychonomic bulletin & review • 2005
View 16 Excerpts
Highly Influenced

References

Publications referenced by this paper.
Showing 1-10 of 104 references

Flexibility versus generalizability in model selection.

Psychonomic bulletin & review • 2003
View 10 Excerpts
Highly Influenced

An introduction to the bootstrap

B. Efron, R. J. Tibshirani
1993
View 5 Excerpts
Highly Influenced

Bootstrap methods: Another look at the jackknife

B. Efron
Annals of Statistics, • 1979
View 4 Excerpts
Highly Influenced

Similar Papers

Loading similar papers…