Journal of Mathematical Psychology volume 48, issue 1, P28-50 2004 DOI: 10.1016/ View full text
Eric-Jan Wagenmakers, Roger Ratcliff, Pablo Gomez, Geoffrey J. Iverson

Abstract: 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 parameter values …

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