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/

Global: Zendy Plus annual

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

Global: Zendy Plus monthly

Global: Zendy Tools annual

Global: Zendy Tools monthly

Global: Zendy Free Plan

We generalize Levene's test for variance (scale) heterogeneity between $k$groups for more complex data, which includes sample correlation and groupmembership uncertainty. Following a two-stage regression framework, we showthat least absolute deviation regression must be used in the stage 1 analysisto ensure a correct asymptotic $\chi^2_{k-1}/(k-1)$ distribution of thegeneralized scale ($gS$) test statistic. We then show that the proposed $gS$test is independent of the generalized location test, under the joint nullhypothesis of no mean and no variance heterogeneity. Consequently, wegeneralize the recently proposed joint location-scale ($gJLS$) test valuable insettings where there is an interaction effect, but one interacting variable isnot available. We evaluate the proposed method via an extensive simulationstudy, and two genetic association application studies.

A Generalized Levene's Scale Test for Variance Heterogeneity in the Presence of Sample Correlation and Group Uncertainty