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