Version 7.4 includes additional features to handle complex-sampled survey assessments and automatic handling of a variety of real-world data problems (e.g., booklet effects in balanced incomplete block designs, skewed test information functions). Parameter estimation uses a Stochastic Gradient Descent approach using the EM algorithm with ensemble estimation of paramaters (sufficient statistics and Newton-Raphson) during the maximization step with a normal prior imposed on the b-parameters. Use the 64-bit version to handle very large data sets.
You may also need to download and install .Net Framework update.
IATA is a software package for analysing psychometric and educational assessment data. It performs factor analysis, item response theory (IRT) scaling and calibration, differential item functioning (DIF) analysis, computer aided test development, equating, IRT-based standard setting, score conditioning, and plausible value generation. IATA is provided free by Fernando Cartwright and was developed with a great deal of support from many people, with special thanks to Vincent Greaney.