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Analysing model fit of psychometric process models: An overview, a new test and an application to the diffusion model
Author(s) -
Ranger Jochen,
Kuhn JörgTobias,
Szardenings Carsten
Publication year - 2017
Publication title -
british journal of mathematical and statistical psychology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 3.157
H-Index - 51
eISSN - 2044-8317
pISSN - 0007-1102
DOI - 10.1111/bmsp.12082
Subject(s) - model validation , process (computing) , test (biology) , diffusion , diffusion process , computer science , econometrics , psychology , statistics , mathematics , data science , innovation diffusion , programming language , geology , thermodynamics , paleontology , physics , knowledge management
Cognitive psychometric models embed cognitive process models into a latent trait framework in order to allow for individual differences. Due to their close relationship to the response process the models allow for profound conclusions about the test takers. However, before such a model can be used its fit has to be checked carefully. In this manuscript we give an overview over existing tests of model fit and show their relation to the generalized moment test of Newey ( Econometrica , 53, 1985, 1047) and Tauchen ( J. Econometrics , 30, 1985, 415). We also present a new test, the Hausman test of misspecification (Hausman, Econometrica , 46, 1978, 1251). The Hausman test consists of a comparison of two estimates of the same item parameters which should be similar if the model holds. The performance of the Hausman test is evaluated in a simulation study. In this study we illustrate its application to two popular models in cognitive psychometrics, the Q‐diffusion model and the D‐diffusion model (van der Maas, Molenaar, Maris, Kievit, & Boorsboom, Psychol Rev ., 118, 2011, 339; Molenaar, Tuerlinckx, & van der Maas, J. Stat. Softw ., 66, 2015, 1). We also compare the performance of the test to four alternative tests of model fit, namely the M 2 test (Molenaar et al ., J. Stat. Softw ., 66, 2015, 1), the moment test (Ranger et al ., Br. J. Math. Stat. Psychol ., 2016) and the test for binned time (Ranger & Kuhn, Psychol. Test. Asess. Model ., 56, 2014b, 370). The simulation study indicates that the Hausman test is superior to the latter tests. The test closely adheres to the nominal Type I error rate and has higher power in most simulation conditions.