Map an item model, item parameters, and person trait score into a
information vector
Create a graded response model
Unidimensional dichotomous item models (1PL, 2PL, and 3PL).
Knox Cube Test dataset
Create a nominal response model
Create a multiple-choice response model
Find the point where an item provides mean maximum information
Liking for Science dataset
Rescale item parameters
Length of the item parameter vector
Write a flexMIRT PRM file
The ogive constant
Map an item model, item parameters, and person trait score into a
probability vector
Item derivatives with respect to ability
Calculate item and person Rasch fit statistics
The base class for multi-dimensional response probability functions.
The base class for 1 dimensional response probability functions.
Compute S-Chi-squared fit statistic for a set of items
Convert an IRT item model name to an ID
Calculate standardized residuals
Read a flexMIRT PRM file
Map an item model, item parameters, and person trait score into a
probability vector
Retrieve a description of the given parameter
Calculate residuals
The multiple-choice response item model (both unidimensional and
multidimensional models have the same parameterization).
Length of the item model vector
Compute S-Chi-squared fit statistic for 1 item
The unidimensional graded response item model.
Multidimensional dichotomous item models (M1PL, M2PL, and M3PL).
rpf - Response Probability Functions
The base class for response probability functions.
Randomly sample response patterns given a list of items
The base class for multi-dimensional graded response probability
functions.
The multidimensional graded response item model.
Create a dichotomous response model
Calculate cell central moments
Generates item parameters
The nominal response item model (both unidimensional and
multidimensional models have the same parameterization).
The base class for 1 dimensional graded response probability functions.
Find the point where an item provides mean maximum information
Item parameter derivatives