Structural Equation Modeling
Hierarchical Linear Modeling
Item Response Theory Applications
Multivariate Applications
System Requirements
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System Requirements:

• All Windows software can be installed on a PC running Windows 95 or better. 

• Free LISREL 8.7 Student edition 
• LISREL main menu 

• New in HLM 
• Student edition 
• HLM main menu 

Available for Windows and Unix.

 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 include 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 include 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 include 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 include syntax and annotated examples.