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rpf (version 0.49)

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

0.49

License

GPL (>= 3)

Maintainer

Joshua Pritikin

Last Published

November 19th, 2015

Functions in rpf (0.49)

ptw2011.gof.test

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

Class rpf.mdim.mcm

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

Create a nominal response model

toFactorLoading

Convert response function slopes to factor loadings

sumScoreEAPTest

Conduct the sum-score EAP distribution test

Compute the ordinal gamma association statistic

orderCompletely

Order a data.frame by missingness and all columns

Class rpf.mdim.drm

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

Compute the S fit statistic for a set of items

Class rpf.1dim.graded

The base class for 1 dimensional graded response probability functions.

Class rpf.mdim.graded

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

Rescale item parameters

rpf.1dim.stdresidual

Calculate standardized residuals

Description of LSAT7 data

Multinomial fit test

Liking for Science dataset

fromFactorThreshold

Convert factor thresholds to response function intercepts

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

Convert an OpenMx MxModel object into an IFA group

itemOutcomeBySumScore

Produce an item outcome by observed sum-score table

Find the point where an item provides mean maximum information

An introduction

rpf - Response Probability Functions

compressDataFrame

Compress a data frame into unique rows and frequencies

Write a flexMIRT PRM file

The base class for multi-dimensional response probability functions.

Calculate item and person Rasch fit statistics

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

Read a flexMIRT PRM file

omitMostMissing

Omit items with the most missing data

The base class for 1 dimensional response probability functions.

Create a graded response model

Transform from [0,1] to the reals

Length of the item parameter vector

Compute the sum-score EAP table

Generates item parameters

Monte-Carlo test for cross-tabulation tables

Create a dichotomous response model

rpf.1dim.residual

Calculate residuals

Length of the item model vector

Randomly sample response patterns given a list of items

The ogive constant

observedSumScore

Compute the observed sum-score

Create a similar item specification with the given number of factors

Class rpf.mdim.grm

The multidimensional graded response item model.

Find the point where an item provides mean maximum information

Identify the columns with most missing data

ChenThissen1997

Computes local dependence indices for all pairs of items

toFactorThreshold

Convert response function intercepts to factor thresholds

Strip data and scores from an IFA group

Item derivatives with respect to the location in the latent space

Description of LSAT6 data

Tabulate data.frame rows

Omit the given items

Class rpf.1dim.drm

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

Class rpf.mdim.nrm

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

rpf.1dim.moment

Calculate cell central moments

Create a multiple-choice response model

Compute EAP scores

expandDataFrame

Expand summary table of patterns and frequencies

Convert an rpf item model name to an ID

The base class for response probability functions.

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

fromFactorLoading

Convert factor loadings to response function slopes

Knox Cube Test dataset

Compute the S fit statistic for 1 item

Class rpf.1dim.grm

The unidimensional graded response item model.

Item parameter derivatives

Retrieve a description of the given parameter