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https://doi.org/10.1198/016214504000001303

has been cited by the following article:

• TITLE: Computational Precision of the Power Function for Conditional Tests of Assumptions of the Rasch Model

  AUTHORS: Clemens Draxler, Jan Philipp Nolte

  KEYWORDS: Conditional Tests, Conditional Probability Distribution, Hypergeometric Distribution, Power Function, Random Sampling, Rasch Model

  JOURNAL NAME: Open Journal of Statistics, Vol.8 No.6, November 15, 2018

  ABSTRACT: Draxler and Zessin [1] derived the power function for a class of conditional tests of assumptions of a psychometric model known as the Rasch model and suggested an MCMC approach developed by Verhelst [2] for the numerical approximation of the power of the tests. In this contribution, the precision of the Verhelst approach is investigated and compared with an exact sampling procedure proposed by Miller and Harrison [3] for which the discrete probability distribution to be sampled from is exactly known. Results show no substantial differences between the two numerical procedures and quite accurate power computations. Regarding the question of computing time the Verhelst approach will have to be considered much more efficient.