Estimation of dynamic models?

[Staffan Betnér]

There are some dynamic irt models that model the transition from one time point to another as a first-order Markov process, allowing different sets of questions in each time point (suitable for, for example, models of parliamentary voting). One example is Martin and Quinn's model in Dynamic Ideal Point Estimation via Markov Chain Monte Carlo for the U.S. Supreme Court, 1953-1999. That model is available in MCMCpack, but only for the one-dimensional case. I wonder whether it is possible to estimate such models in mirt (and thus allowing for several item types, which would be amazing).

[Phil Chalmers]

I can't say I'm familiar with these models. Could you provide a pdf reference, and possible the probability equations used to estimate this model? Cheers.

Phil

On Mon, Oct 10, 2016 at 3:43 PM, Staffan Betnér <sta...@betner.nu> wrote:

There are some dynamic irt models that model the transition from one time point to another as a first-order Markov process, allowing different sets of questions in each time point (suitable for, for example, models of parliamentary voting). One example is Martin and Quinn's model in Dynamic Ideal Point Estimation via Markov Chain Monte Carlo for the U.S. Supreme Court, 1953-1999. That model is available in MCMCpack, but only for the one-dimensional case. I wonder whether it is possible to estimate such models in mirt (and thus allowing for several item types, which would be amazing).

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[Seongho Bae]

Hi, Phil.

Andrew D. Martin and Kevin M. Quinn. 2002. "Dynamic Ideal Point Estimation via Markov Chain Monte Carlo for the U.S. Supreme Court, 1953-1999." Political Analysis. 10: 134-153. URI: http://pan.oxfordjournals.org/content/10/2/134.abstract

and Errata is here: http://pan.oxfordjournals.org/content/24/1/e1

Seongho

2016년 10월 11일 화요일 오후 11시 29분 52초 UTC+9, Phil Chalmers 님의 말:

Phil

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