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  • In psychological tests, the time needed to respond to the items provides collateral information about the latent traits of the test takers. This, however, requires a measurement model that incorporates the response times in addition to the responses. Such a measurement model is usually based on a full specification of the response time distribution. In the present article, we suggest a novel modeling approach that requires fewer assumptions. In the approach, the responses are modeled with a unidimensional two-parameter logistic model. The single response times are summed to the scale-specific total testing time which is then related to the latent trait of the two-parameter logistic model via a smooth adaptive Gaussian mixture (SAGM) model. The approach can be justified against the background of the bivariate generalized linear item response theory modeling framework (Molenaar, Tuerlinckx, & van der Maas, 2015a). Its utility is investigated in two simulation studies and an empirical example. (xsd:string)
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  • https://doi.org/10.1027/1614-2241/a000181. (GESIS Panel) (xsd:string)
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  • 2019 (xsd:gyear)
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  • 2019 (xsd:gyear)
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  • 10.1027/1614-2241/a000181 ()
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  • 185 (xsd:string)
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  • 1614-2241 ()
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  • Using Response Times as Collateral Information About Latent Traits in Psychological Tests (xsd:string)
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  • In Methodology, 15(4), 185-196, 2019 (xsd:string)
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  • 15 (xsd:string)