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rpf (version 0.45)

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

20,661

Version

0.45

License

GPL (>= 3)

Maintainer

Joshua Pritikin

Last Published

May 26th, 2015

Functions in rpf (0.45)

Class rpf.1dim.grm

The unidimensional graded response item model.

Read a flexMIRT PRM file

Description of LSAT6 data

Randomly sample response patterns given a list of items

Compute the ordinal gamma association statistic

itemOutcomeBySumScore

Produce an item outcome by observed sum-score table

Item parameter derivatives

Create a similar item specification with the given number of factors

Generates item parameters

Create a dichotomous response model

Convert an rpf item model name to an ID

Strip data and scores from an IFA group

fromFactorLoading

Convert factor loadings to response function slopes

Class rpf.mdim.mcm

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

Identify the columns with most missing data

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).

Rescale item parameters

Find the point where an item provides mean maximum information

Class rpf.1dim.graded

The base class for 1 dimensional graded response probability functions.

Length of the item model vector

Length of the item parameter vector

Compute the S fit statistic for a set of items

Knox Cube Test dataset

The base class for response probability functions.

fromFactorThreshold

Convert factor thresholds to response function intercepts

toFactorLoading

Convert response function slopes to factor loadings

The ogive constant

Compute the sum-score EAP table

Omit the given items

rpf.1dim.stdresidual

Calculate standardized residuals

Create a nominal response model

Calculate item and person Rasch fit statistics

Find the point where an item provides mean maximum information

omitMostMissing

Omit items with the most missing data

Create a graded response model

Create a multiple-choice response model

Class rpf.mdim.drm

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

Retrieve a description of the given parameter

Compute the S fit statistic for 1 item

Monte-Carlo test for cross-tabulation tables

The base class for 1 dimensional response probability functions.

orderCompletely

Order a data.frame by missingness and all columns

observedSumScore

Compute the observed sum-score

The base class for multi-dimensional response probability functions.

Description of LSAT7 data

Write a flexMIRT PRM file

ChenThissen1997

Computes local dependence indices for all pairs of items

compressDataFrame

Compress a data frame into unique rows and frequencies

rpf.1dim.residual

Calculate residuals

ptw2011.gof.test

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

sumScoreEAPTest

Conduct the sum-score EAP distribution test

An introduction

rpf - Response Probability Functions

Tabulate data.frame rows

Class rpf.mdim.grm

The multidimensional graded response item model.

Liking for Science dataset

rpf.1dim.moment

Calculate cell central moments

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

Class rpf.mdim.graded

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

toFactorThreshold

Convert response function intercepts to factor thresholds

Compute EAP scores

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

Item derivatives with respect to the location in the latent space

Transform from [0,1] to the reals

expandDataFrame

Expand summary table of patterns and frequencies

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

Multinomial fit test

Convert an OpenMx MxModel object into an IFA group