Abstract
Friedman’s chi-square test is a non-parametric statistical test for r treatments across n trials to assess the null hypothesis that there is no treatment effect. We use Stein’s method with an exchangeable pair coupling to derive a bound on the distance between the distribution of Friedman’s statistic and its limiting chi-square distribution, measured using smooth test functions. Our bound is of the optimal order n−1, and also has an optimal dependence on the parameter r, in that the bound tends to zero if and only if r/n→0. From this bound, we deduce a Kolmogorov distance bound that decays to zero under the weaker condition r1/2/n→0.
| Original language | English |
|---|---|
| Journal | Bernoulli |
| Publication status | Accepted/In press - 7 Jul 2022 |
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