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

Discrete but ordered covariates are quite common in applied statistics, andsome regularized fitting procedures have been proposed for proper handling ofordinal predictors in statistical modeling. In this study, we show howquadratic penalties on adjacent dummy coefficients of ordinal predictorsproposed in the literature can be incorporated in the framework of generalizedadditive models, making tools for statistical inference developed thereavailable for ordinal predictors as well. Motivated by an application fromneonatal medicine, we discuss whether results obtained when constructingconfidence intervals and testing significance of smooth terms in generalizedadditive models are useful with ordinal predictors/penalties as well.

Statistical Inference for Ordinal Predictors in Generalized Linear and Additive Models with Application to Bronchopulmonary Dysplasia