rpf (version 0.7)

rpf.grm: Create a graded response model and associated hyperparameters.

Description

This function instantiates a graded response model. Bayesian priors are only used to generate plausible random parameters.

Usage

rpf.grm(numOutcomes = 2, dimensions = 1,
    multidimensional)

Arguments

numOutcomes

The number of choices available

dimensions

the number of dimensions

multidimensional

whether to use a multidimensional model. Defaults to TRUE when dimensions>1 and FALSE when dimensions==1.

Value

• an item model

Details

The graded response model was designed for a item with a series of dependent parts where a higher score implies that easier parts of the item were surmounted. If there is any chance your polytomous item has independent parts then consider rpf.gpcm. If your categories cannot cross then the graded response model provides a little more information than the GPCM. Stronger a priori assumptions offer provide more power at the cost of flexibility.