Computing Critical Values of Exact Tests by Incorporating Monte Carlo Simulations Combined with Statistical Tables.

ABSTRACT: Various exact tests for statistical inference are available for powerful and accurate decision rules provided that corresponding critical values are tabulated or evaluated via Monte Carlo methods. This article introduces a novel hybrid method for computing p-values of exact tests by combining Monte Carlo simulations and statistical tables generated a priori. To use the data from Monte Carlo generations and tabulated critical values jointly, we employ kernel density estimation within Bayesian-type procedures. The p-values are linked to the posterior means of quantiles. In this framework, we present relevant information from the Monte Carlo experiments via likelihood-type functions, whereas tabulated critical values are used to reflect prior distributions. The local maxi

SUBMITTER: Vexler A 

PROVIDER: S-EPMC4809026 | biostudies-literature | 2014 Dec

REPOSITORIES: biostudies-literature