SSI, Inc. offers academic and non-academic (production and commercial) licenses for its IRT software products.
Academic licenses for BILOG-MG 3, MULTILOG 7, PARSCALE 4, and TESTFACT 4 for Windows are available separately.
Academic licenses for the IRT Software Suite for Windows (comprised of BILOG-MG 3, MULTILOG 7, PARSCALE 4, and TESTFACT 4 for Windows) are also available.
Academic licenses apply to end users that intend to use the software exclusively
Academic licenses can be ordered using the online PDF order forms providing an academic email address
Non-academic licenses apply to end users that intend to use the software for assessment
Non-academic license agreements are prepared on a case to case (individual) basis. For details, see: http://www.ssicentral.com/ordering/academic.html
Graphical user interface
Efficient analysis of binary items including multiple
choice or short-answer items scored right, wrong, omitted,
or not-presented
Capable of large scale production analysis, and
handling of multiple groups
Performs item analysis and scoring of any number
of subtests or subscales
Non-equivalent groups equating
Vertical equating of test forms
Differential item functioning (DIF)
Detection and correction for parameter trends over
time (DRIFT)
Calibration and Scoring of tests in two-stage testing
procedures
Estimation of latent ability or proficiency distributions
Provision for items inserted in tests to estimate
item statistics, but not included in calculation of examinee
scores ("variant items")
Item fit statistics, theoretical and empirical reliability
Information curves and reliabilities for putative
test forms
Presentation quality IRT graphics, can be imported
in Word, Access, etc.
Detailed online HELP documentation includes description
of interface, syntax, and examples.
Easy to use graphical user interface
One, two and three-parameter logistic models
Samejima's model for graded responses
Bock's model for nominal (non-ordered) responses
Steinberg's model for multiple-choice items
Handling of multiple-alternative items, such as
multiple-choice tests or Likert-type attitude questionnaires
Scoring of items with multiple alternatives
Differential item functioning (DIF)
Handling of data from several populations simultaneously
Analysis of mixtures of items types
Testing of item parameters across groups
Handling of equality constraints and fixed parameters
Presentation quality IRT graphics, can be imported
in Word, Access, etc.
Detailed online HELP documentation includes description
of interface, syntax, and examples.
The flexibility and the wealth of information provided
by this program have kept it in regular use by researchers
around the world
One, two, and three-parameter logistic models
Samejima's model for graded responses
Master's partial credit model
Generalized partial credit model
Analysis of rating scale items such as open-ended
essay questions
Analysis of multiple-choice items
Differential item functioning (DIF)
Analysis of mixtures of item types
Rater's-effect analysis
Multiple-group polytomous item response models
Presentation quality IRT graphics, can be imported
in Word, Access, etc.
Detailed online HELP documentation includes syntax
and examples.
Marginal maximum likelihood (MML) exploratory factor
analysis and classical item analysis of binary data
Computes tetrachoric correlations, principal factor solution,
classical item descriptive statistics, fractile tables and
plots
Handles up to 10 factors using numerical quadrature: up
to 5 for non-adaptive and up to 10 for adaptive quadrature
Handles up to 15 factors using Monte Carlo integration
techniques
Varimax (orthogonal) and PROMAX (oblique) rotation of
factor loadings
Handles an important form of confirmatory factor analysis
known as "bifactor" analysis: Factor pattern consists
of one main factor plus group factors
Simulation of responses to items based on user specified
parameters
Correction for guessing and not-reached items
Allows imposition of constraints on item parameter estimates
Handles omitted and not-presented items
Detailed online HELP documentation includes syntax and
annotated examples.
