irt_coef help file
The installed help file, rendered for the web
This page is generated from irt_coef.sthlp by build.do, so it matches the installed version. In Stata, type help irt_coef.
Title
irt_coef – Calculates y* standardized coefficients (discrimination parameters) for binary and ordinal IRT models
General syntax
irt_coef [varlist] , options
Overview
irt_coef calculates y* standardized coefficients (discrimination parameters) for binary and ordinal IRT models. The raw coefficient, standard error, and p-value are also reported alongside the y* standardized coefficient.
Required Option for gsem models
| Option | Description |
|---|---|
latent(name) |
is required if gsem was used to fit the model of interest. This is the name of the latent variable that is the indepenent variable (the items are the dependent variables [i.e. the y’s]). 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(name) |
specifies the name of saved model estimates to use. See estimates store for saving model estimates. By default, irt_coef 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. |
sort |
orders the rows of the table based on the values of the y* standardized coefficients. |
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 charity
irt grm ta1 ta2 ta3 ta4 ta5
irt_coef, help
gsem (Theta -> ta1 ta2 ta3 ta4 ta5, ologit), var(Theta@1)
irt_coef, latent(Theta)Citation
Please cite the use of irt_coef as:
Mize, Trenton D. 2024. “irt_coef: Stata command for y*-standardized coefficients in item response theory models.” https://www.trentonmize.com/software/irt_coef
References
Bartholomew, David J., Fiona Steele, Irini Moustaki, and Jane I. Galbrath. 2008. Analysis of Multivariate Social Science Data. Second Edition. CRC Press.
Long, J. Scott. 1997. Regression Models for Categorical and Limited Dependent Variables. Sage.
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