Title: An Asymptotically Efficient Metropolis-Hastings Sampler for Bayesian Inference in Large-Scale Educational Measuremen,
Abstract: This paper discusses a Metropolis-Hastings algorithm developed by
\citeA{MarsmanIsing}. The algorithm is derived from first principles, and it is
proven that the algorithm becomes more efficient with more data and meets the
growing demands of large scale educational measurement.