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 Tools annual

Global: Zendy Free Plan

Global: Zendy Tools monthly

Global: Zendy Plus monthly

Longitudinal studies are often conducted to explore the cohort and ageeffects in many scientific areas. The within cluster correlation structureplays a very important role in longitudinal data analysis. This is because notonly can an estimator be improved by incorporating the within clustercorrelation structure into the estimation procedure, but also the withincluster correlation structure can sometimes provide valuable insights inpractical problems. For example, it can reveal the correlation strengths amongthe impacts of various factors. Motivated by data typified by a set fromBangladesh pertinent to the use of contraceptives, we propose a random effectvarying-coefficient model, and an estimation procedure for the within clustercorrelation structure of the proposed model. The estimation procedure isoptimization-free and the proposed estimators enjoy asymptotic normality undermild conditions. Simulations suggest that the proposed estimation ispracticable for finite samples and resistent against mild forms of modelmisspecification. Finally, we analyze the data mentioned above with the newrandom effect varying-coefficient model together with the proposed estimationprocedure, which reveals some interesting sociological dynamics.

Estimation of the covariance matrix of random effects in longitudinal studies