English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Zendy Plus

Presents the access of premium content as premium feature

Premium Content

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Zendy Tools

Zendy Open

Randomization tests are based on a re-randomization of existing data to gaindata-dependent critical values that lead to exact hypothesis tests underspecial circumstances. However, it is not always possible to re-randomize datain accordance to the physical randomization from which the data has beenobained. As a consequence, most statistical tests cannot control the type Ierror probability. Still, similarly as the bootstrap, data re-randomization canbe used to improve the type I error control. However, no general asymptotictheory under weak null hypotheses has been developed for such randomizationtests yet. It is the aim of this paper to provide a conveniently applicabletheory on the asymptotic validity of randomization tests with asymptoticallynormal test statistics. Similarly, confidence intervals will be developed.  This will be achieved by creating a link between two well-established fieldsin mathematical statistics: empirical processes and inference based onrandomization via algebraic groups. A broadly applicable conditional weakconvergence theorem is developed for empirical processes that are based onrandomized observations. Random elements of an algebraic group are applied tothe data vectors from which the randomized version of a statistic is derived.Combining a variant of the functional delta-method with a suitablestudentization of the statistic, asymptotically exact hypothesis tests isdeduced, while the finite sample exactness property under group-invariantsub-hypotheses is preserved. The methodology is exemplified with: the Pearsoncorrelation coefficient, a Mann-Whitney effect based on right-censored paireddata, and a competing risks analysis. The practical usefulness of theapproaches is assessed through simulation studies and an application to datafrom patients suffering from diabetic retinopathy.

Randomized Empirical Processes by Algebraic Groups, and Tests for Weak Null Hypotheses