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rpf (version 0.8)

Response Probability Functions

Description

The purpose of this package is to factor out logic and math common to Item Response Theory fitting, diagnostics, and analysis. It is envisioned as core support code suitable for more specialized IRT packages to build upon. Complete access to optimized C functions are made available with R_RegisterCCallable.

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Version

Install

install.packages('rpf')

Monthly Downloads

23,955

Version

0.8

License

GPL (>= 3)

Maintainer

Joshua Pritikin

Last Published

March 13th, 2013

Functions in rpf (0.8)

Class rpf.mdim.drm

Multidimensional dichotomous item models (M1PL, M2PL, and M3PL).
rpf.id_of

Convert an IRT item model name to an ID
mentalsilence

Mental silence dataset
rpf.ogive

The ogive constant
rpf.grm

Create a graded response model and associated hyperparameters.
rpf.logprob

Map an item model, item parameters, and person trait score into a probability vector
rpf.numSpec

Length of the item model vector
rpf.info

Map an item model, item parameters, and person trait score into a information vector
Class rpf.1dim

The base class for 1 dimensional response probability functions.
rpf.ot2000.chisq

Compute S-Chi-squared fit statistic for a set of items
rpf.drm

Create a dichotomous response model and associated hyperparameters.
Class rpf.1dim.drm

Unidimensional dichotomous item models (1PL, 2PL, and 3PL).
rpf.mcm

Create a multiple-choice response model and associated hyperparameters.
rpf.nrm

Create a nominal response model and associated hyperparameters.
rpf.1dim.stdresidual

Calculate standardized residuals
rpf.GaussHermiteData

Compute Gauss-Hermite quadrature rule
Class rpf.base

The base class for response probability functions.
rpf.gradient

Item parameter gradients
rpf.1dim.moment

Calculate cell moments
Class rpf.1dim.gpcm

The unidimensional generalized partial credit item model.
rpf.numParam

Length of the item parameter vector
rpf.mean.info

Find the point where an item provides mean maximum information
science

Liking for Science dataset
Class rpf.1dim.grm

The unidimensional graded response item model.
rpf.gpcm

Create a generalized partial credit model and associated hyperparameters.
rpf.prob

Map an item model, item parameters, and person trait score into a probability vector
rpf.ot2000.chisq1

Compute S-Chi-squared fit statistic for 1 item
rpf.rparam

Generates item parameters
Class rpf.mdim.nrm

The nominal response item model (both unidimensional and multidimensional models have the same parameterization).
Class rpf.mdim

The base class for multi-dimensional response probability functions.
Class rpf.mdim.graded

The base class for multi-dimensional graded response probability functions.
Class rpf.mdim.mcm

The multiple-choice response item model (both unidimensional and multidimensional models have the same parameterization).
Class rpf.mdim.grm

The multidimensional graded response item model.
Class rpf.1dim.graded

The base class for 1 dimensional graded response probability functions.
Class rpf.mdim.gpcm

The multidimensional generalized partial credit item model.
rpf.1dim.fit

Calculate item and person fit statistics
rpf.mean.info1

Find the point where an item provides mean maximum information
rpf.sample

Randomly sample response patterns given a list of items
rpf.1dim.residual

Calculate residuals
rpf.prior

Log likelihood of the item model parameters given the Bayesian prior
An introduction

rpf - Response Probability Functions