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