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