Vector Psychometric Group (VPG) is proud to offer cutting-edge software for web-based data collection and item response data analysis.
With your renewable VPG subscription, you are entitled to many more benefits in comparison to previous licensing models. Click here to view a side-by-side comparison chart of features.
Currently we offer no native Mac version of any of our programs currently available. However, if you have a dual-boot set-up or a Windows emulator, any of our programs should run without issues. Note that we can only provide support for using the software and are unable to provide guidance on setting up a Mac to allow for a program to be usable. Parallels Desktop is the most frequently used of the emulators. VirtualBox is a free alternative from Oracle, but it can be very slow compared to Parallels.
flexMIRT® is software specifically designed for the analysis of item response data, such as what can be obtained from a quality of life measure, attitude survey, or academic test. It is able to accommodate a wide variety of IRT models to factor structures that are both unidimensional and multidimensional (e.g., the items measure more than one concept). flexMIRT® provides a wide variety of item and model fit statistics and indices for evaluating results and produces several different types of IRT-based scores, depending on user request. While flexMIRT® is primarily a confirmatory modeling program, it has capabilities for performing EFA with analytic rotations as well.
IRTPRO™ is an advanced application for item calibration and test scoring using item response theory (IRT). It comes with an intuitive graphical user interface and offers built-in production quality IRT graphics. Suitable for educators, students, researchers, and assessment organizations, IRTPRO™ has become increasingly popular in the educational, psychological, social, and health sciences. IRTPRO™ handles any combination of unidimensional or multidimensional versions of popular IRT models, in multiple groups. The users may choose from a number of sophisticated estimation algorithms for item and person parameters. User-defined parameter restrictions and the availability of many test statistics facilitate statistical inference for IRT modeling.