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 Tools annual

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 Tools monthly

Global: Zendy Plus monthly

Presents the access of premium content as premium feature

Premium Content

Global: Zendy Plus annual

Global: Zendy Free Plan

Over the past decades, linear mixed models have attracted considerableattention in various fields of applied statistics. They are popular wheneverclustered, hierarchical or longitudinal data are investigated. Nonetheless,statistical tools for valid simultaneous inference for mixed parameters arerare. This is surprising because one often faces inferential problems beyondthe pointwise examination of fixed or mixed parameters. For example, there isan interest in a comparative analysis of cluster-level parameters orsubject-specific estimates in studies with repeated measurements. We discussmethods for simultaneous inference assuming a linear mixed model. Specifically,we develop simultaneous prediction intervals as well as multiple testingprocedures for mixed parameters. They are useful for joint considerations orcomparisons of cluster-level parameters. We employ a consistent bootstrapapproximation of the distribution of max-type statistic to construct our tools.The numerical performance of the developed methodology is studied in simulationexperiments and illustrated in a data example on household incomes in smallareas.

Simultaneous inference for linear mixed model parameters with an application to small area estimation