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rpf (version 0.3)

rpf.drm: Create a dichotomous response model and associated hyperparameters.

Description

This function instantiates a dichotomous response model. The discrimination prior defaults to the lognormal distribution with meanlog=0 and sdlog=.5. The guessing prior is the beta distribution. See the source code for details. For discussion on the choice of these Bayesian priors see Baker & Kim (2004, pp. 187-188).

Usage

rpf.drm(numChoices = 5, dimensions = 1, D = 1,
    multidimensional)

Arguments

numChoices
the number of choices in the question
dimensions
the number of dimensions
D
defaults to 1 or pass in rpf.ogive
multidimensional
whether to use a multidimensional model. Defaults to TRUE when dimensions>1 and FALSE when dimensions==1.

Value

  • an item model

Details

It is not yet possible to further customize the Bayesian priors. The API will change before the 1.0 release.

References

Baker & Kim (2004). Item Response Theory: Parameter Estimation Techniques. Marcel Dekker, Inc.