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rpf (version 0.52)

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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Install

install.packages('rpf')

Monthly Downloads

20,661

Version

0.52

License

GPL (>= 3)

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Repository

https://github.com/jpritikin/rpf

Maintainer

Joshua Pritikin

Last Published

May 4th, 2016

Functions in rpf (0.52)

Compute the S fit statistic for 1 item

Compute the ordinal gamma association statistic

Item derivatives with respect to the location in the latent space

Class rpf.mdim.graded

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

Knox Cube Test dataset

Compute EAP scores

Description of LSAT7 data

Create a nominal response model

toFactorThreshold

Convert response function intercepts to factor thresholds

Class rpf.1dim.grm

The unidimensional graded response item model.

Class rpf.mdim.drm

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

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

itemOutcomeBySumScore

Produce an item outcome by observed sum-score table

Description of LSAT6 data

The base class for multi-dimensional response probability functions.

Find the point where an item provides mean maximum information

Multinomial fit test

Length of the item model vector

Create a dichotomous response model

Length of the item parameter vector

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

sumScoreEAPTest

Conduct the sum-score EAP distribution test

Create logistic function of a monotonic polynomial (LMP) model

Identify the columns with most missing data

Class rpf.mdim.grm

The multidimensional graded response item model.

Randomly sample response patterns given a list of items

Convert an OpenMx MxModel object into an IFA group

fromFactorThreshold

Convert factor thresholds to response function intercepts

rpf.1dim.residual

Calculate residuals

orderCompletely

Order a data.frame by missingness and all columns

The base class for response probability functions.

Create a similar item specification with the given number of factors

Create a multiple-choice response model

ChenThissen1997

Computes local dependence indices for all pairs of items

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).

Find the point where an item provides mean maximum information

Class rpf.1dim.graded

The base class for 1 dimensional graded response probability functions.

fromFactorLoading

Convert factor loadings to response function slopes

rpf.1dim.stdresidual

Calculate standardized residuals

Read a flexMIRT PRM file

Item parameter derivatives

Retrieve a description of the given parameter

Tabulate data.frame rows

The base class for 1 dimensional response probability functions.

ptw2011.gof.test

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

Create a graded response model

Convert an rpf item model name to an ID

Write a flexMIRT PRM file

compressDataFrame

Compress a data frame into unique rows and frequencies

Class rpf.mdim.nrm

The nominal 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

expandDataFrame

Expand summary table of patterns and frequencies

Strip data and scores from an IFA group

Calculate item and person Rasch fit statistics

An introduction

rpf - Response Probability Functions

toFactorLoading

Convert response function slopes to factor loadings

Rescale item parameters

omitMostMissing

Omit items with the most missing data

Omit the given items

rpf.1dim.moment

Calculate cell central moments

Compute the S fit statistic for a set of items

Monte-Carlo test for cross-tabulation tables

Class rpf.1dim.drm

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

The ogive constant

Liking for Science dataset

observedSumScore

Compute the observed sum-score

Compute the sum-score EAP table

Class rpf.1dim.lmp

Unidimensional logistic function of a monotonic polynomial.

Generates item parameters