Response Probability Functions

Documentation for package ‘rpf’ version 1.0.14

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rpf - Response Probability Functions

-- A --

An introduction	rpf - Response Probability Functions
as.IFAgroup	Convert an OpenMx MxModel object into an IFA group

-- B --

bestToOmit

Identify the columns with most missing data

-- C --

chen.thissen.1997	Computes local dependence indices for all pairs of items
ChenThissen1997	Computes local dependence indices for all pairs of items
Class rpf.1dim	The base class for 1 dimensional response probability functions.
Class rpf.1dim.drm	Unidimensional dichotomous item models (1PL, 2PL, and 3PL).
Class rpf.1dim.gpcmp	Unidimensional generalized partial credit monotonic polynomial.
Class rpf.1dim.graded	The base class for 1 dimensional graded response probability functions.
Class rpf.1dim.grm	The unidimensional graded response item model.
Class rpf.1dim.grmp	Unidimensional graded response monotonic polynomial.
Class rpf.1dim.lmp	Unidimensional logistic function of a monotonic polynomial.
Class rpf.base	The base class for response probability functions.
Class rpf.mdim	The base class for multi-dimensional response probability functions.
Class rpf.mdim.drm	Multidimensional dichotomous item models (M1PL, M2PL, and M3PL).
Class rpf.mdim.graded	The base class for multi-dimensional graded response probability functions.
Class rpf.mdim.grm	The multidimensional graded response item model.
Class rpf.mdim.mcm	The multiple-choice response item model (both unidimensional and multidimensional models have the same parameterization).
Class rpf.mdim.nrm	The nominal response item model (both unidimensional and multidimensional models have the same parameterization).
collapseCategoricalCells	Collapse small sample size categorical frequency counts
compressDataFrame	Compress a data frame into unique rows and frequencies
crosstabTest	Monte-Carlo test for cross-tabulation tables

-- E --

EAPscores	Compute Expected A Posteriori (EAP) scores
expandDataFrame	Expand summary table of patterns and frequencies

-- F --

fromFactorLoading	Convert factor loadings to response function slopes
fromFactorThreshold	Convert factor thresholds to response function intercepts

-- I --

itemOutcomeBySumScore

Produce an item outcome by observed sum-score table

-- K --

kct	Knox Cube Test dataset
kct.items	Knox Cube Test dataset
kct.people	Knox Cube Test dataset

-- L --

logit	Transform from [0,1] to the reals
LSAT6	Description of LSAT6 data
LSAT7	Description of LSAT7 data

-- M --

multinomialFit

Multinomial fit test

-- O --

observedSumScore	Compute the observed sum-score
omitItems	Omit the given items
omitMostMissing	Omit items with the most missing data
orderCompletely	Order a data.frame by missingness and all columns
ordinal.gamma	Compute the ordinal gamma association statistic

-- P --

ptw2011.gof.test

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

-- R --

read.flexmirt	Read a flexMIRT PRM file
rpf.1dim-class	The base class for 1 dimensional response probability functions.
rpf.1dim.drm-class	Unidimensional dichotomous item models (1PL, 2PL, and 3PL).
rpf.1dim.fit	Calculate item and person Rasch fit statistics
rpf.1dim.gpcmp-class	Unidimensional generalized partial credit monotonic polynomial.
rpf.1dim.graded-class	The base class for 1 dimensional graded response probability functions.
rpf.1dim.grm-class	The unidimensional graded response item model.
rpf.1dim.grmp-class	Unidimensional graded response monotonic polynomial.
rpf.1dim.lmp-class	Unidimensional logistic function of a monotonic polynomial.
rpf.1dim.moment	Calculate cell central moments
rpf.1dim.residual	Calculate residuals
rpf.1dim.stdresidual	Calculate standardized residuals
rpf.base-class	The base class for response probability functions.
rpf.dLL	Item parameter derivatives
rpf.dLL-method	Item parameter derivatives
rpf.drm	Create a dichotomous response model
rpf.dTheta	Item derivatives with respect to the location in the latent space
rpf.dTheta-method	Item derivatives with respect to the location in the latent space
rpf.gpcmp	Create monotonic polynomial generalized partial credit (GPC-MP) model
rpf.grm	Create a graded response model
rpf.grmp	Create monotonic polynomial graded response (GR-MP) model
rpf.id_of	Convert an rpf item model name to an ID
rpf.info	Map an item model, item parameters, and person trait score into a information vector
rpf.lmp	Create logistic function of a monotonic polynomial (LMP) model
rpf.logprob	Map an item model, item parameters, and person trait score into a probability vector
rpf.logprob-method	Map an item model, item parameters, and person trait score into a probability vector
rpf.mcm	Create a multiple-choice response model
rpf.mdim-class	The base class for multi-dimensional response probability functions.
rpf.mdim.drm-class	Multidimensional dichotomous item models (M1PL, M2PL, and M3PL).
rpf.mdim.graded-class	The base class for multi-dimensional graded response probability functions.
rpf.mdim.grm-class	The multidimensional graded response item model.
rpf.mdim.mcm-class	The multiple-choice response item model (both unidimensional and multidimensional models have the same parameterization).
rpf.mdim.nrm-class	The nominal response item model (both unidimensional and multidimensional models have the same parameterization).
rpf.mean.info	Find the point where an item provides mean maximum information
rpf.mean.info1	Find the point where an item provides mean maximum information
rpf.modify	Create a similar item specification with the given number of factors
rpf.modify-method	Create a similar item specification with the given number of factors
rpf.nrm	Create a nominal response model
rpf.numParam	Length of the item parameter vector
rpf.numParam-method	Length of the item parameter vector
rpf.numSpec	Length of the item model vector
rpf.numSpec-method	Length of the item model vector
rpf.ogive	The ogive constant
rpf.paramInfo	Retrieve a description of the given parameter
rpf.paramInfo-method	Retrieve a description of the given parameter
rpf.prob	Map an item model, item parameters, and person trait score into a probability vector
rpf.prob-method	Map an item model, item parameters, and person trait score into a probability vector
rpf.rescale	Rescale item parameters
rpf.rescale-method	Rescale item parameters
rpf.rparam	Generates item parameters
rpf.rparam-method	Generates item parameters
rpf.sample	Randomly sample response patterns given a list of items
rpf_numParam_wrapper	Length of the item parameter vector
rpf_numSpec_wrapper	Length of the item model vector
rpf_paramInfo_wrapper	Retrieve a description of the given parameter

-- S --

science	Liking for Science dataset
sfif	Liking for Science dataset
sfpf	Liking for Science dataset
sfsf	Liking for Science dataset
sfxf	Liking for Science dataset
SitemFit	Compute the S fit statistic for a set of items
SitemFit1	Compute the S fit statistic for 1 item
stripData	Strip data and scores from an IFA group
sumScoreEAP	Compute the sum-score EAP table
sumScoreEAPTest	Conduct the sum-score EAP distribution test

-- T --

tabulateRows	Tabulate data.frame rows
toFactorLoading	Convert response function slopes to factor loadings
toFactorThreshold	Convert response function intercepts to factor thresholds

-- W --

write.flexmirt

Write a flexMIRT PRM file

-- misc --

$-method	The base class for response probability functions.
$<--method	The base class for response probability functions.
_rpf_dLL	Item parameter derivatives
_rpf_dTheta	Item derivatives with respect to the location in the latent space
_rpf_logprob	Map an item model, item parameters, and person trait score into a probability vector
_rpf_prob	Map an item model, item parameters, and person trait score into a probability vector
_rpf_rescale	Rescale item parameters