Response Probability Functions
Convert an OpenMx MxModel object into an IFA group
Identify the columns with most missing data
Computes local dependence indices for all pairs of items
Collapse small sample size categorical frequency counts
Compress a data frame into unique rows and frequencies
Monte-Carlo test for cross-tabulation tables
Compute Expected A Posteriori (EAP) scores
Expand summary table of patterns and frequencies
Convert factor loadings to response function slopes
Convert factor thresholds to response function intercepts
Produce an item outcome by observed sum-score table
Transform from [0,1] to the reals
Multinomial fit test
Compute the observed sum-score
Omit the given items
Omit items with the most missing data
Order a data.frame by missingness and all columns
Compute the ordinal gamma association statistic
Compute the P value that the observed and expected tables come from th...
Read a flexMIRT PRM file
The base class for 1 dimensional response probability functions.
Unidimensional dichotomous item models (1PL, 2PL, and 3PL).
Calculate item and person Rasch fit statistics
Unidimensional generalized partial credit monotonic polynomial.
The base class for 1 dimensional graded response probability functions...
The unidimensional graded response item model.
Unidimensional graded response monotonic polynomial.
Unidimensional logistic function of a monotonic polynomial.
Calculate cell central moments
Calculate residuals
Calculate standardized residuals
The base class for response probability functions.
Item parameter derivatives
Create a dichotomous response model
Item derivatives with respect to the location in the latent space
Create monotonic polynomial generalized partial credit (GPC-MP) model
Create a graded response model
Create monotonic polynomial graded response (GR-MP) model
Convert an rpf item model name to an ID
Map an item model, item parameters, and person trait score into a info...
rpf - Response Probability Functions
Create logistic function of a monotonic polynomial (LMP) model
Map an item model, item parameters, and person trait score into a prob...
Create a multiple-choice response model
The base class for multi-dimensional response probability functions.
Multidimensional dichotomous item models (M1PL, M2PL, and M3PL).
The base class for multi-dimensional graded response probability funct...
The multidimensional graded response item model.
The multiple-choice response item model (both unidimensional and multi...
The nominal response item model (both unidimensional and multidimensio...
Find the point where an item provides mean maximum information
Find the point where an item provides mean maximum information
Create a similar item specification with the given number of factors
Create a nominal response model
Length of the item parameter vector
Length of the item model vector
The ogive constant
Retrieve a description of the given parameter
Map an item model, item parameters, and person trait score into a prob...
Rescale item parameters
Generates item parameters
Randomly sample response patterns given a list of items
Compute the S fit statistic for a set of items
Compute the S fit statistic for 1 item
Strip data and scores from an IFA group
Compute the sum-score EAP table
Conduct the sum-score EAP distribution test
Tabulate data.frame rows
Convert response function slopes to factor loadings
Convert response function intercepts to factor thresholds
Write a flexMIRT PRM file
Factor out logic and math common to Item Factor Analysis fitting, diagnostics, and analysis. It is envisioned as core support code suitable for more specialized IRT packages to build upon. Complete access to optimized C functions are made available with R_RegisterCCallable(). This software is described in Pritikin & Falk (2020) <doi:10.1177/0146621620929431>.