statistics

New Equivalence Tests for Approximate Independence in Contingency Tables

arXiv:2607.11130 · doi:10.3390/stats2020018

summary

The paper proposes new equivalence tests for assessing approximate independence in two‑way contingency tables, using asymptotic critical values and a bootstrap‑enhanced estimator of boundary points to improve finite‑sample performance, with simulations and real‑data applications provided in an R package.

Abstract

We introduce new equivalence tests for approximate independence in two-way contingency tables. The critical values are calculated asymptotically. The finite sample performance of the tests is improved by means of the bootstrap. An estimator of boundary points is developed to make the bootstrap based tests statistically efficient and computationally feasible. We compare the performance of the proposed tests for different table sizes by simulation. Then we apply the tests to real data sets. The tests are implemented in R and available online, see [https://github.com/TestingEquivalence/EquivalenceTestIndependenceR].

Topics & keywords

#contingency tables#independence testing#equivalence testing#bootstrap methods#asymptotic theoryequivalence testapproximate independencetwo-way tablebootstrapboundary estimatorR implementation
New Equivalence Tests for Approximate Independence in Contingency Tables · wovepaper