classify: Classification Accuracy and Consistency under IRT models.

IRT classification uses the probability that candidates of a given ability, will answer correctly questions of a specified difficulty to calculate the probability of their achieving every possible score in a test. Due to the IRT assumption of conditional independence (that is every answer given is assumed to depend only on the latent trait being measured) the probability of candidates achieving these potential scores can be expressed by multiplication of probabilities for item responses for a given ability. Once the true score and the probabilities of achieving all other scores have been determined for a candidate the probability of their score lying in the same category as that of their true score (classification accuracy), or the probability of consistent classification in a category over administrations (classification consistency), can be calculated.

Package details

AuthorDr Chris Wheadon and Dr Ian Stockford
MaintainerDr Chris Wheadon <[email protected]>
LicenseGPL (>= 2)
Package repositoryView on CRAN
Installation Install the latest version of this package by entering the following in R:

Try the classify package in your browser

Any scripts or data that you put into this service are public.

classify documentation built on May 29, 2017, 7:49 p.m.