Published On: 27/06/2016|Categories: 2013–2017, Vol.37 (2), Vol.37 (2016)|

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This note is about Bayes EAP scoring in the class of oblique linear and nonlinear item response models that can be parameterized as factor analytic models. For these models, we propose an improved implementation approach that (a) provides more detailed and informative output, and (b) uses more prior information from the calibration stage. Overall, we discuss the limitations of EAP estimation as it is implemented in most available programs, provide a technical account of the basic methodology and proposed improvements, implement the proposal in the freely available FACTOR program, and illustrate how it works with FACTOR-based output.

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