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- 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.
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- 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.
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- 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.
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- 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.
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- IRT: Fundamentals of item response theory workshop: June 16–20, 2008 by Michael C. Edwards,, Lawrence, Kansas. New!
- IRT: Principles and applications workshop: July 28-August 2, 2008 by Ronald K. Hambleton,
Lisa A. Keller, Craig S. Wells, & Jennifer Randall, Amherst, MA.
 
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