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rpf (version 0.51)

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

0.51

License

GPL (>= 3)

Maintainer

Joshua Pritikin

Last Published

December 16th, 2015

Functions in rpf (0.51)

Compute the S fit statistic for 1 item

The base class for multi-dimensional response probability functions.

Rescale item parameters

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

Retrieve a description of the given parameter

Identify the columns with most missing data

Create a graded response model

Omit the given items

Class rpf.1dim.drm

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

Randomly sample response patterns given a list of items

fromFactorThreshold

Convert factor thresholds to response function intercepts

orderCompletely

Order a data.frame by missingness and all columns

Compute the ordinal gamma association statistic

Liking for Science dataset

observedSumScore

Compute the observed sum-score

Create a multiple-choice response model

compressDataFrame

Compress a data frame into unique rows and frequencies

expandDataFrame

Expand summary table of patterns and frequencies

Class rpf.1dim.grm

The unidimensional graded response item model.

The base class for response probability functions.

Class rpf.mdim.graded

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

Monte-Carlo test for cross-tabulation tables

Find the point where an item provides mean maximum information

rpf.1dim.residual

Calculate residuals

Find the point where an item provides mean maximum information

Tabulate data.frame rows

toFactorThreshold

Convert response function intercepts to factor thresholds

Multinomial fit test

Convert an rpf item model name to an ID

Create a similar item specification with the given number of factors

Compute the sum-score EAP table

ChenThissen1997

Computes local dependence indices for all pairs of items

sumScoreEAPTest

Conduct the sum-score EAP distribution test

Write a flexMIRT PRM file

omitMostMissing

Omit items with the most missing data

Description of LSAT6 data

itemOutcomeBySumScore

Produce an item outcome by observed sum-score table

Read a flexMIRT PRM file

Length of the item parameter vector

Item parameter derivatives

Convert an OpenMx MxModel object into an IFA group

Transform from [0,1] to the reals

Class rpf.mdim.mcm

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

Class rpf.mdim.grm

The multidimensional graded response item model.

rpf.1dim.moment

Calculate cell central moments

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

Length of the item model vector

Description of LSAT7 data

Compute the S fit statistic for a set of items

rpf.1dim.stdresidual

Calculate standardized residuals

Class rpf.1dim.graded

The base class for 1 dimensional graded response probability functions.

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

Create a dichotomous response model

ptw2011.gof.test

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

Item derivatives with respect to the location in the latent space

Class rpf.1dim.lmp

Unidimensional logistic function of a monotonic polynomial.

toFactorLoading

Convert response function slopes to factor loadings

Compute EAP scores

Calculate item and person Rasch fit statistics

Create logistic function of a monotonic polynomial (LMP) model

Create a nominal response model

The ogive constant

Class rpf.mdim.drm

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

Generates item parameters

Strip data and scores from an IFA group

Knox Cube Test dataset

An introduction

rpf - Response Probability Functions

fromFactorLoading

Convert factor loadings to response function slopes

The base class for 1 dimensional response probability functions.

Class rpf.mdim.nrm

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