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rpf (version 0.39)

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

0.39

License

GPL (>= 3)

Maintainer

Joshua Pritikin

Last Published

September 22nd, 2014

Functions in rpf (0.39)

orderCompletely

Order a data.frame by missingness and all columns

Compute the S fit statistic for a set of items

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

The ogive constant

Randomly sample response patterns given a list of items

Write a flexMIRT PRM file

Compute the sum-score EAP table

Create a dichotomous response model

An introduction

rpf - Response Probability Functions

Multinomial fit test

Length of the item parameter vector

Class rpf.mdim.nrm

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

ptw2011.gof.test

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

The base class for response probability functions.

Generates item parameters

Monte-Carlo test for cross-tabulation tables

Compute the S fit statistic for 1 item

Compute the ordinal gamma association statistic

Read a flexMIRT PRM file

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).

Convert an rpf item model name to an ID

Find the point where an item provides mean maximum information

Compute EAP scores

Knox Cube Test dataset

Calculate item and person Rasch fit statistics

itemOutcomeBySumScore

Produce an item outcome by observed sum-score table

Transform from [0,1] to the reals

Create a multiple-choice response model

ChenThissen1997

Computes local dependence indices for all pairs of items

The base class for 1 dimensional response probability functions.

Item parameter derivatives

observedSumScore

Compute the observed sum-score

sumScoreEAPTest

Conduct the sum-score EAP distribution test

omitMostMissing

Omit items with the most missing data

Create a nominal response model

Item derivatives with respect to the location in the latent space

Rescale item parameters

compressDataFrame

Compress a data frame into unique rows and frequencies

Class rpf.1dim.drm

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

Create a graded response model

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

Class rpf.1dim.graded

The base class for 1 dimensional graded response probability functions.

Liking for Science dataset

rpf.1dim.moment

Calculate cell central moments

expandDataFrame

Expand summary table of patterns and frequencies

Tabulate data.frame rows

Find the point where an item provides mean maximum information

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

Convert an OpenMx MxModel object into an IFA group

rpf.1dim.stdresidual

Calculate standardized residuals

Class rpf.mdim.grm

The multidimensional graded response item model.

The base class for multi-dimensional response probability functions.

Length of the item model vector

Create a similar item specification with the given number of factors

Retrieve a description of the given parameter

Class rpf.1dim.grm

The unidimensional graded response item model.

rpf.1dim.residual

Calculate residuals

Class rpf.mdim.drm

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