Dear fellow Stata users.
Thanks to Kit Baum a new package uirt is now available for download from SSC.
Description: uirt is a Stata module for estimating variety of unidimensional IRT models (2PLM, 3PLM, GRM, PCM, GPCM). It features multi-group modelling, DIF analysis, extended graphical item fit analysis and generating plausible values (PVs) conditioned via latent regression. uirt implements the EM algorithm (Dempster, Laird & Rubin, 1977) in the form of marginal maximum likelihood estimation (MML) proposed by Bock & Aitkin (1981) with normal Gauss-Hermite quadrature. LR test is used for DIF testing and model based P-DIF effect size measures are provided (Wainer, 1993). Generating PVs is performed by adapting a MCMC method developed for IRT models by Patz & Junker (1999). Unconditioned PVs are used to plot observed response proportions against the item characteristic curves allowing for detailed graphical item fit analysis.
To install, in Stata type: ssc install uirt. For detailed description of options end references type help uirt after installing.
I hope this package to be especially useful in the following instances:
Regards,
Bartek
Thanks to Kit Baum a new package uirt is now available for download from SSC.
Description: uirt is a Stata module for estimating variety of unidimensional IRT models (2PLM, 3PLM, GRM, PCM, GPCM). It features multi-group modelling, DIF analysis, extended graphical item fit analysis and generating plausible values (PVs) conditioned via latent regression. uirt implements the EM algorithm (Dempster, Laird & Rubin, 1977) in the form of marginal maximum likelihood estimation (MML) proposed by Bock & Aitkin (1981) with normal Gauss-Hermite quadrature. LR test is used for DIF testing and model based P-DIF effect size measures are provided (Wainer, 1993). Generating PVs is performed by adapting a MCMC method developed for IRT models by Patz & Junker (1999). Unconditioned PVs are used to plot observed response proportions against the item characteristic curves allowing for detailed graphical item fit analysis.
To install, in Stata type: ssc install uirt. For detailed description of options end references type help uirt after installing.
I hope this package to be especially useful in the following instances:
- If you are a Stata 13 or a Stata 12 user and want to perform IRT analysis (I plan to enable it to run on Stata 10 in future releases)
- If you are a Stata 14 user and:
- want to fit a multi-group IRT model
Code:
use http://www.stata-press.com/data/r14/masc2.dta *2PLM/GRM are default models uirt q*,gr(female)
- want to analyze for differential item functioning with IRT P-DIF effect measures
Code:
*using the above masc2.dta uirt q*,gr(female) dif(q*) *to view a compact summary of DIF analysis: mat l e(dif_results)
- want to graphically inspect item fit in your IRT model
Code:
use http://www.stata-press.com/data/r14/alike.dta *this will save ICCs with observed proportions in your working directory uirt v*,icc *you can see that the “v3” item exhibits some misfit:
- want to generate plausible values
Code:
*using the above alike.dta uirt v*, pv(2) theta *we can see a lack of shrinkage in comparison with EAP estimate: sum pv* theta
- have a large dataset
Regards,
Bartek
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