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