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rpf (version 0.28)

Response Probability Functions

Description

The purpose of this package is to factor out logic and math common to Item Factor Analysis 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

0.28

License

GPL (>= 3)

Maintainer

Joshua Pritikin

Last Published

April 3rd, 2014

Functions in rpf (0.28)

Create a dichotomous response model

Transform from [0,1] to the reals

Liking for Science dataset

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

The base class for multi-dimensional response probability functions.

chen.thissen.1997

Computes local dependence indices for all pairs of items

rpf.ot2000.chisq1

Compute S-Chi-squared fit statistic for 1 item

Calculate item and person Rasch fit statistics

Create a similar item specification with the given number of factors

Class rpf.mdim.drm

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

ptw2011.gof.test

Compute the P value that the observed and expected tables come from the same distribution

rpf.1dim.moment

Calculate cell central moments

Class rpf.mdim.mcm

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

Find the point where an item provides mean maximum information

rpf.1dim.stdresidual

Calculate standardized residuals

Create a nominal response model

Randomly sample response patterns given a list of items

Class rpf.1dim.grm

The unidimensional graded response item model.

The base class for response probability functions.

Knox Cube Test dataset

Class rpf.1dim.graded

The base class for 1 dimensional graded response probability functions.

Length of the item parameter vector

Length of the item model vector

Item derivatives with respect to ability

Map an item model, item parameters, and person trait score into a information vector

Class rpf.mdim.grm

The multidimensional graded response item model.

An introduction

rpf - Response Probability Functions

rpf.1dim.residual

Calculate residuals

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

Unpack a two-tier model

Retrieve a description of the given parameter

The base class for 1 dimensional response probability functions.

Convert an IRT item model name to an ID

Create a graded response model

Rescale item parameters

Item parameter derivatives

Compute the ordinal gamma association statistic

Class rpf.mdim.graded

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

The ogive constant

Write a flexMIRT PRM file

Generates item parameters

Create a multiple-choice response model

Find the point where an item provides mean maximum information

rpf.ot2000.chisq

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

Read a flexMIRT PRM file

Class rpf.mdim.nrm

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

Class rpf.1dim.drm

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