Compute the S fit statistic for 1 item
Compute the ordinal gamma association statistic
Item derivatives with respect to the location in the latent space
The base class for multi-dimensional graded response probability
functions.
Knox Cube Test dataset
Compute EAP scores
Description of LSAT7 data
Create a nominal response model
Convert response function intercepts to factor thresholds
The unidimensional graded response item model.
Multidimensional dichotomous item models (M1PL, M2PL, and M3PL).
Map an item model, item parameters, and person trait score into a
information vector
Produce an item outcome by observed sum-score table
Description of LSAT6 data
The base class for multi-dimensional response probability functions.
Find the point where an item provides mean maximum information
Multinomial fit test
Length of the item model vector
Create a dichotomous response model
Length of the item parameter vector
Map an item model, item parameters, and person trait score into a
probability vector
Conduct the sum-score EAP distribution test
Create logistic function of a monotonic polynomial (LMP) model
Identify the columns with most missing data
The multidimensional graded response item model.
Randomly sample response patterns given a list of items
Convert an OpenMx MxModel object into an IFA group
Convert factor thresholds to response function intercepts
Calculate residuals
Order a data.frame by missingness and all columns
The base class for response probability functions.
Create a similar item specification with the given number of factors
Create a multiple-choice response model
Computes local dependence indices for all pairs of items
Transform from [0,1] to the reals
The multiple-choice response item model (both unidimensional and
multidimensional models have the same parameterization).
Find the point where an item provides mean maximum information
The base class for 1 dimensional graded response probability functions.
Convert factor loadings to response function slopes
Calculate standardized residuals
Read a flexMIRT PRM file
Item parameter derivatives
Retrieve a description of the given parameter
Tabulate data.frame rows
The base class for 1 dimensional response probability functions.
Compute the P value that the observed and expected tables come from the same distribution
Create a graded response model
Convert an rpf item model name to an ID
Write a flexMIRT PRM file
Compress a data frame into unique rows and frequencies
The nominal 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
Expand summary table of patterns and frequencies
Strip data and scores from an IFA group
Calculate item and person Rasch fit statistics
rpf - Response Probability Functions
Convert response function slopes to factor loadings
Rescale item parameters
Omit items with the most missing data
Omit the given items
Calculate cell central moments
Compute the S fit statistic for a set of items
Monte-Carlo test for cross-tabulation tables
Unidimensional dichotomous item models (1PL, 2PL, and 3PL).
The ogive constant
Liking for Science dataset
Compute the observed sum-score
Compute the sum-score EAP table
Unidimensional logistic function of a monotonic polynomial.
Generates item parameters