irt_me help file

The installed help file, rendered for the web

This page is generated from irt_me.sthlp by build.do, so it matches the installed version. In Stata, type help irt_me.

Title

irt_me – Calculates marginal effects for the latent variable (Theta) after IRT models

General syntax

irt_me [varlist] , options

Overview

irt_me calculates marginal effects for the latent variable (theta) after an IRT model. The latent variable is the independent variable; the variables specifed in the varlist are the observed items which are the dependent variables in an IRT model. If no varlist is specified, irt_me calculates marginal effects for theta across all of the observed items.

irt_me supports all models that can be estimated using the Stata irt commands and also models for continuous and count items (regress, poisson, and nbreg). A mix of different item types is also allowed (e.g., a mix of binary and ordinal items).

Required Option for gsem models

Option Description
latent(string) is required if gsem was used to fit the model of interest. This is the name of the latent variable you wish to obtain marginal effects for. The latent( ) option should not be used if the model was fit with the irt command as irt automatically names the latent variable Theta.

Options

Option Description
model(string) specifies the name of saved model estimates to use. See estimates store for saving model estimates. By default, irt_me will use the IRT/GSEM estimates in memory. If the relevant model estimates are not in memory, you must specify their name.
decimals(#) changes the number of decimal places reported for the statistics. The default is 3. Any integer between 1 - 8 is allowed.
start(#) specifies the starting value for the prediction used in the calculation of the marginal effect. The default is -0.5 for a default marginal effect estimate of a centered +1 unit change.
end(#) specifies the ending value for the prediction used in the calculation of the marginal effect. The default is 0.5 for a default marginal effect estimate of a centered +1 unit change.
range calculates marginal effects across the trimmed range of the predicted values of the latent variable theta. Predictions are made at the 1st percentile of theta (start) and at the 99th percentile of theta (end)
title(string) changes the title of the table of results. A default title is automatically included.
help prints footnotes below the table describing what the columns in the table represent.

Examples

webuse masc1
irt 2pl q1 q2 q3 q4 q5
irt_me, help
gsem (Theta -> q1 q2 q3 q4 q5, logit), var(Theta@1)
irt_me, latent(Theta)

Authorship

irt_me is written by Trenton D Mize (Departments of Sociology & Statistics [by courtesy] & The Methodology Center at Purdue University). Questions can be sent to tmize@purdue.edu

Citation

Please cite the use of irt_me as:

  • Mize, Trenton D. 2024. “Stata command for marginal effects from item response theory models.” https://www.trentonmize.com/software/irt_me
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