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.