Response Probability Functions

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Documentation for package ‘rpf’ version 0.28

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An introduction-package rpf - Response Probability Functions
$-method The base class for response probability functions.
$<--method The base class for response probability functions.
An introduction rpf - Response Probability Functions
chen.thissen.1997 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.graded The base class for 1 dimensional graded response probability functions.
Class rpf.1dim.grm The unidimensional graded response item model.
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).
kct Knox Cube Test dataset
kct.items Knox Cube Test dataset
kct.people Knox Cube Test dataset
logit Transform from [0,1] to the reals
ordinal.gamma Compute the ordinal gamma association statistic
ptw2011.gof.test Compute the P value that the observed and expected tables come from the same distribution
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.graded-class The base class for 1 dimensional graded response probability functions.
rpf.1dim.grm-class The unidimensional graded response item model.
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 ability
rpf.dTheta-method Item derivatives with respect to ability
rpf.grm Create a graded response model
rpf.id_of Convert an IRT item model name to an ID
rpf.info Map an item model, item parameters, and person trait score into a information vector
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.ot2000.chisq Compute S-Chi-squared fit statistic for a set of items
rpf.ot2000.chisq1 Compute S-Chi-squared fit statistic for 1 item
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_dLL_wrapper Item parameter derivatives
rpf_dTheta_wrapper Item derivatives with respect to ability
rpf_logprob_wrapper Map an item model, item parameters, and person trait score into a probability vector
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
rpf_prob_wrapper Map an item model, item parameters, and person trait score into a probability vector
rpf_rescale_wrapper Rescale item parameters
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
unpack.2tier Unpack a two-tier model
write.flexmirt Write a flexMIRT PRM file