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rpf (version 0.5)

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. Version 1.0 will offer most of the functionality as a C library as well as from this R package.

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Version

Install

install.packages('rpf')

Monthly Downloads

23,955

Version

0.5

License

GPL (>= 3)

Maintainer

Joshua Pritikin

Last Published

December 25th, 2012

Functions in rpf (0.5)

The base class for multi-dimensional response probability functions.

Description of LSAT6 data

The base class for response probability functions.

itemOutcomeBySumScore

Produce an item outcome by observed sum-score table

Class rpf.mdim.graded

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

Class rpf.mdim.grm

The multidimensional graded response item model.

rpf.1dim.residual

Calculate residuals

Convert an OpenMx MxModel object into an IFA group

Randomly sample response patterns given a list of items

rpf.prob wrapper1

Adjust the shape of the arguments for rpf.prob.

Create a similar item specification with the given number of factors

Compute EAP scores

rpf.setLocation

Set location related item parameters

Calculate item and person Rasch fit statistics

fromFactorLoading

Convert factor loadings to response function slopes

Compute the ordinal gamma association statistic

Generates item parameters

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

Find the point where an item provides mean maximum information

An introduction

rpf - Response Probability Functions

Write a flexMIRT PRM file

fromFactorThreshold

Convert factor thresholds to response function intercepts

expandDataFrame

Expand summary table of patterns and frequencies

Compute the S fit statistic for a set of items

Identify the columns with most missing data

ptw2011.gof.test

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

rpf.1dim.stdresidual

Calculate standardized residuals

toFactorThreshold

Convert response function intercepts to factor thresholds

Create a generalized partial credit model and associated hyperparameters.

The base class for 1 dimensional response probability functions.

Create a multiple-choice response model and associated hyperparameters.

Item parameter derivatives

Strip data and scores from an IFA group

observedSumScore

Compute the observed sum-score

Length of the item parameter vector

compressDataFrame

Compress a data frame into unique rows and frequencies

Knox Cube Test dataset

Class rpf.1dim.grm

The unidimensional graded response item model.

Omit the given items

Create a graded response model

Class rpf.mdim.mcm

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

Class rpf.1dim.graded

The base class for 1 dimensional graded response probability functions.

Create logistic function of a monotonic polynomial (LMP) model

Item derivatives with respect to the location in the latent space

sumScoreEAPTest

Conduct the sum-score EAP distribution test

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

Convert an rpf item model name to an ID

Rescale item parameters

ChenThissen1997

Computes local dependence indices for all pairs of items

Class rpf.mdim.nrm

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

Create a nominal response model

Compute the sum-score EAP table

omitMostMissing

Omit items with the most missing data

Monte-Carlo test for cross-tabulation tables

Create a dichotomous response model

rpf.prob wrapper4

Implement rpf.prob in terms of rpf.logprob.

orderCompletely

Order a data.frame by missingness and all columns

Class rpf.1dim.drm

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

Class rpf.1dim.gpcm

The unidimensional generalized partial credit item model.

rpf.getLocation

Extract location related item parameters

rpf.prob wrapper5

Implement rpf.prob in terms of rpf.logprob.

rpf.prob wrapper3

Adjust the shape of the arguments for rpf.prob.

Compute the S fit statistic for 1 item

Length of the item model vector

Read a flexMIRT PRM file

toFactorLoading

Convert response function slopes to factor loadings

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

Class rpf.mdim.drm

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

Description of LSAT7 data

Retrieve a description of the given parameter

Find the point where an item provides mean maximum information

Class rpf.1dim.lmp

Unidimensional logistic function of a monotonic polynomial.

Transform from [0,1] to the reals

Multinomial fit test

The ogive constant

Liking for Science dataset

rpf.1dim.moment

Calculate cell central moments

rpf.startingParam

Initial item parameters

rpf.prob wrapper2

Adjust the shape of the arguments for rpf.prob.

rpf.logprob wrapper3

Adjust the shape of the arguments for rpf.logprob.

Class rpf.mdim.gpcm

The multidimensional generalized partial credit item model.

Tabulate data.frame rows