Order a data.frame by missingness and all columns
Compute the S fit statistic for a set of items
Map an item model, item parameters, and person trait score into a
information vector
The ogive constant
Randomly sample response patterns given a list of items
Write a flexMIRT PRM file
Compute the sum-score EAP table
Create a dichotomous response model
rpf - Response Probability Functions
Multinomial fit test
Length of the item parameter vector
The nominal 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
The base class for response probability functions.
Generates item parameters
Monte-Carlo test for cross-tabulation tables
Compute the S fit statistic for 1 item
Compute the ordinal gamma association statistic
Read a flexMIRT PRM file
The base class for multi-dimensional graded response probability
functions.
The multiple-choice response item model (both unidimensional and
multidimensional models have the same parameterization).
Convert an rpf item model name to an ID
Find the point where an item provides mean maximum information
Compute EAP scores
Knox Cube Test dataset
Calculate item and person Rasch fit statistics
Produce an item outcome by observed sum-score table
Transform from [0,1] to the reals
Create a multiple-choice response model
Computes local dependence indices for all pairs of items
The base class for 1 dimensional response probability functions.
Item parameter derivatives
Compute the observed sum-score
Conduct the sum-score EAP distribution test
Omit items with the most missing data
Create a nominal response model
Item derivatives with respect to the location in the latent space
Rescale item parameters
Compress a data frame into unique rows and frequencies
Unidimensional dichotomous item models (1PL, 2PL, and 3PL).
Create a graded response model
Map an item model, item parameters, and person trait score into a
probability vector
The base class for 1 dimensional graded response probability functions.
Liking for Science dataset
Calculate cell central moments
Expand summary table of patterns and frequencies
Tabulate data.frame rows
Find the point where an item provides mean maximum information
Map an item model, item parameters, and person trait score into a
probability vector
Convert an OpenMx MxModel object into an IFA group
Calculate standardized residuals
The multidimensional graded response item model.
The base class for multi-dimensional response probability functions.
Length of the item model vector
Create a similar item specification with the given number of factors
Retrieve a description of the given parameter
The unidimensional graded response item model.
Calculate residuals
Multidimensional dichotomous item models (M1PL, M2PL, and M3PL).