Explore the relationship between unobserved latent characteristics such as mathematical aptitude and the probability of correctly answering test questions (items). Or explore the relationship between unobserved health and self-reported responses to questions about mobility, independence, and other health-affected activities. IRT can be used to create measures of such unobserved traits or place individuals on a scale measuring the trait. It can also be used to select the best items for measuring a latent trait. IRT models are available for binary, graded, rated, partial-credit, and nominal response items. Visualize the relationships using item characteristic curves, and measure overall test performance using test information functions. And much more.


BINARY RESPONSE MODELS

  • One-parameter logistic (1PL)
  • Two-parameter logistic (2PL)
  • Three-parameter logistic (3PL)

 

ORDINAL RESPONSE MODELS

  • Graded response
  • Partial credit
  • Generalized partial credit
  • Rating scale

 

CATEGORICAL RESPONSE MODEL

  • Nominal response

 

HYBRID MODELS WITH DIFFERING RESPONSE TYPES

 

MULTIPLE-GROUP IRT MODELS

  • Allow parameters to vary across groups
  • Constrain parameters across groups to be equal
  • Available for all IRT models
  • Test for differences across groups

 

GRAPHS

  • Item characteristic curves and boundary characteristic curves
    • Plot midpoint probabilities
  • Category characteristic curves
  • Test characteristic curve
    • Plot expected score for a specified ability level
    • Plot ability for a specified expected score
  • Item information functions
  • Test information function
    • Plot the standard error
  • Fully customizable graphs
  • Save your graphed results as datasets for future use

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DIF DIAGNOSTICS

  • Mantel–Haenszel test
  • Logistic regression test
  • IRT model-based test

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CONTROL PANEL INTERFACE

  • Access all IRT features
  • Easily select response type and item variables
  • Even create hybrid models
  • Estimate models
  • Select and customize graphs
  • Manage reporting of results

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CONTROL HOW YOUR OUTPUT IS DISPLAYED

  • Sort by difficulty
  • Sort by discrimination
  • Group estimates by type or by item
  • Show results only for selected items
  • Compare IRT estimates across groups

POSTESTIMATION SELECTOR

  • View and run all postestimation features for your command
  • Automatically updated as estimation commands are run