Transform from [0,1] to the reals
Multidimensional dichotomous item models (M1PL, M2PL, and M3PL).
Create a multiple-choice response model
Map an item model, item parameters, and person trait score into a
probability vector
Read a flexMIRT PRM file
The nominal response item model (both unidimensional and
multidimensional models have the same parameterization).
Generates item parameters
Unpack a two-tier model
Create a similar item specification with the given number of factors
Retrieve a description of the given parameter
Liking for Science dataset
Computes local dependence indices for all pairs of items
Calculate residuals
Compute the P value that the observed and expected tables come from the same distribution
Calculate standardized residuals
rpf - Response Probability Functions
The base class for multi-dimensional response probability functions.
Find the point where an item provides mean maximum information
Compute the ordinal gamma association statistic
Create a graded response model
Knox Cube Test dataset
Write a flexMIRT PRM file
Compute S-Chi-squared fit statistic for 1 item
Map an item model, item parameters, and person trait score into a
information vector
Length of the item model vector
Map an item model, item parameters, and person trait score into a
probability vector
Rescale item parameters
Find the point where an item provides mean maximum information
Calculate cell central moments
The base class for 1 dimensional graded response probability functions.
Convert an IRT item model name to an ID
Create a nominal response model
The unidimensional graded response item model.
Item derivatives with respect to ability
Unidimensional dichotomous item models (1PL, 2PL, and 3PL).
The multidimensional graded response item model.
Randomly sample response patterns given a list of items
The base class for multi-dimensional graded response probability
functions.
The ogive constant
Item parameter derivatives
Calculate item and person Rasch fit statistics
The base class for response probability functions.
The multiple-choice response item model (both unidimensional and
multidimensional models have the same parameterization).
The base class for 1 dimensional response probability functions.
Create a dichotomous response model
Length of the item parameter vector
Compute S-Chi-squared fit statistic for a set of items