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rpf (version 0.38)

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

0.38

License

GPL (>= 3)

Maintainer

Joshua Pritikin

Last Published

September 4th, 2014

Functions in rpf (0.38)

Create a dichotomous response model

Compute the S fit statistic for 1 item

Create a multiple-choice response model

Create a nominal response model

Class rpf.mdim.nrm

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

Rescale item parameters

Convert an OpenMx MxModel object into an IFA group

omitMostMissing

Omit items with the most missing data

Class rpf.mdim.drm

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

Length of the item parameter vector

Class rpf.1dim.grm

The unidimensional graded response item model.

Tabulate data.frame rows

orderCompletely

Order a data.frame by missingness and all columns

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

Length of the item model vector

Class rpf.mdim.graded

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

Class rpf.mdim.grm

The multidimensional graded response item model.

Monte-Carlo test for cross-tabulation tables

Transform from [0,1] to the reals

ChenThissen1997

Computes local dependence indices for all pairs of items

The base class for 1 dimensional response probability functions.

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

rpf.1dim.moment

Calculate cell central moments

The base class for response probability functions.

Item derivatives with respect to the location in the latent space

Compute EAP scores

Read a flexMIRT PRM file

Class rpf.1dim.graded

The base class for 1 dimensional graded response probability functions.

Knox Cube Test dataset

Find the point where an item provides mean maximum information

observedSumScore

Compute the observed sum-score

Create a similar item specification with the given number of factors

Find the point where an item provides mean maximum information

rpf.1dim.stdresidual

Calculate standardized residuals

Class rpf.mdim.mcm

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

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

An introduction

rpf - Response Probability Functions

Compute the sum-score EAP table

Randomly sample response patterns given a list of items

The base class for multi-dimensional response probability functions.

Compute the ordinal gamma association statistic

Convert an rpf item model name to an ID

The ogive constant

Class rpf.1dim.drm

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

rpf.1dim.residual

Calculate residuals

Item parameter derivatives

sumScoreEAPTest

Conduct the sum-score EAP distribution test

Write a flexMIRT PRM file

Compute the S fit statistic for a set of items

Multinomial fit test

Calculate item and person Rasch fit statistics

Create a graded response model

Retrieve a description of the given parameter

Liking for Science dataset

itemOutcomeBySumScore

Produce an item outcome by observed sum-score table

compressDataFrame

Compress a data frame into unique rows and frequencies

ptw2011.gof.test

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

expandDataFrame

Expand summary table of patterns and frequencies

Generates item parameters