Binary response models

One-parameter logistic (1PL)

Two-parameter logistic (2PL)

Three-parameter logistic (3PL)

Watch One-parameter logistic (1PL) models.
Watch Two-parameter logistic (2PL) models.
Watch Three-parameter logistic (3PL) models


Ordinal response models

Graded response

Partial credit

Generalized partial credit

Rating scale

Watch Graded response (GRM) models.

Watch Rating scale (RSM) models.


Categorical response model

Nominal response

Watch Nominal response (NRM) models.


Hybrid models with differing response types



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



DIF diagnostics

Mantel–Haenszel test

Logistic regression test



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



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



Postestimation Selector

View and run all postestimation features for your command

Automatically updated as estimation commands are run

Watch Postestimation Selector.


Additional resources

Watch IRT (item response theory) models.