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From |
Swati Agiwal <agiwa001@umn.edu> |

To |
Swati Agiwal <agiwa001@umn.edu>, statalist@hsphsun2.harvard.edu |

Subject |
st: Fitting Ordinal Item response Model using GLLAMM |

Date |
Tue, 28 Aug 2007 16:55:32 CDT |

Hello All, I am using the GLLAMM program in Stata and wanted to know if anyone else is using the same for fitting ordinal item response models. I am fitting a simple one parameter as well as a two parameter item response model. I am interpreting the random effect as the latent variable. However, I am facing difficulties in introducing other explanatory variables into the existing item response models. I have looked through the GLLAMM manual and there arent any similar examples. The current model I am fitting is : g(P(y{i}{j}<s)) = k{s} - b{i} - n{j}...Model(1) where g() is the ordinal probit function. y{i}{j} is the ordinal response for person j on question/item i. k{s} are category thresholds, b{i} are item biases and n{j} are the person specific random intercepts, which I interpret as the latent variables. Model(1) is easy to fit in GLLAMM and is well documented in Chapter 8 of the GLLAMM manual. To this i want to incorporate: n{j}= a*w1{j}+ c*w2{j} + q{j} That is, the latent variable n{j} is itself a function of person j specific characteristics, say education w1{j} and income w2{j} and a new latent variable q{j}. a and c are coefficients of the explanatory variables w1 and w2. Thus the final model that i want to fit is : g(P(y{i}{j}<s)) = k{s} - b{i} - a*w1{j} - c*w2{j} - q{j}...Model(2) I am using all the items (87 of them) and all the persons (203 of them) together is estimating this model. If any does have an idea or suggestion as to how to fit Model(2) in GLLAMM please do let me know. Thanks in advance, Swati * * For searches and help try: * http://www.stata.com/support/faqs/res/findit.html * http://www.stata.com/support/statalist/faq * http://www.ats.ucla.edu/stat/stata/

**Follow-Ups**:**Re: st: Fitting Ordinal Item response Model using GLLAMM***From:*"Stas Kolenikov" <skolenik@gmail.com>

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