%0 Journal Article
%T Computational Precision of the Power Function for Conditional Tests of Assumptions of the Rasch Model
%A Clemens Draxler
%A Jan Philipp Nolte
%J Open Journal of Statistics
%P 873-884
%@ 2161-7198
%D 2018
%I Scientific Research Publishing
%R 10.4236/ojs.2018.86058
%X Draxler
and Zessin</span></span><span style=\"font-family:Verdana;\"><span style=\"font-family:Verdana;\"><span style=\"font-family:Verdana;\"> [1]</span></span></span><span style=\"font-family:Verdana;\"><span style=\"font-family:Verdana;\"><span style=\"font-family:Verdana;\"> 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</span></span></span><span style=\"font-family:Verdana;\"><span style=\"font-family:Verdana;\"><span style=\"font-family:Verdana;\"> [2] </span></span></span><span style=\"font-family:Verdana;\"><span style=\"font-family:Verdana;\"><span style=\"font-family:Verdana;\">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</span></span></span><span style=\"font-family:Verdana;\"><span style=\"font-family:Verdana;\"><span style=\"font-family:Verdana;\"> [3]</span></span></span><span style=\"font-family:Verdana;\"><span style=\"font-family:Verdana;\"><span style=\"font-family:Verdana;\"> 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.
%K Conditional Tests
%K Conditional Probability Distribution
%K Hypergeometric Distribution
%K Power Function
%K Random Sampling
%K Rasch Model
%U http://www.scirp.org/journal/PaperInformation.aspx?PaperID=88484