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rpf (version 0.35)

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

0.35

License

GPL (>= 3)

Maintainer

Joshua Pritikin

Last Published

June 30th, 2014

Functions in rpf (0.35)

ChenThissen1997

Computes local dependence indices for all pairs of items

Class rpf.mdim.drm

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

ptw2011.gof.test

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

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

orderCompletely

Order a data.frame by missingness and all columns

Class rpf.mdim.graded

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

Compute EAP scores

Calculate item and person Rasch fit statistics

Compute the S fit statistic for 1 item

Convert an rpf item model name to an ID

rpf.1dim.stdresidual

Calculate standardized residuals

The ogive constant

Length of the item parameter vector

Compute the ordinal gamma association statistic

Find the point where an item provides mean maximum information

Class rpf.mdim.nrm

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

Find the point where an item provides mean maximum information

Item parameter derivatives

expandDataFrame

Expand summary table of patterns and frequencies

Item derivatives with respect to the location in the latent space

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

Compute the sum-score EAP table

Multinomial fit test

compressDataFrame

Compress a data frame into unique rows and frequencies

Randomly sample response patterns given a list of items

Retrieve a description of the given parameter

The base class for response probability functions.

Tabulate data.frame rows

Create a graded response model

Read a flexMIRT PRM file

Create a multiple-choice response model

Class rpf.mdim.grm

The multidimensional graded response item model.

Monte-Carlo test for cross-tabulation tables

Create a dichotomous response model

Generates item parameters

The base class for multi-dimensional response probability functions.

itemOutcomeBySumScore

Produce an item outcome by observed sum-score table

Transform from [0,1] to the reals

rpf.1dim.residual

Calculate residuals

Compute the S fit statistic for a set of items

observedSumScore

Compute the observed sum-score

Liking for Science dataset

Class rpf.1dim.grm

The unidimensional graded response item model.

An introduction

rpf - Response Probability Functions

Class rpf.1dim.graded

The base class for 1 dimensional graded response probability functions.

Rescale item parameters

Class rpf.mdim.mcm

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

Create a nominal response model

Write a flexMIRT PRM file

Length of the item model vector

Create a similar item specification with the given number of factors

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

Knox Cube Test dataset

Class rpf.1dim.drm

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

rpf.1dim.moment

Calculate cell central moments

The base class for 1 dimensional response probability functions.