The search for appropriate statistical methods for hierarchical, multilevel data has been a prominent theme in educational statistics over the past 15 years. As a result of this search, an important ...

Delimitations of hierarchical linear modeling (HLM) were examined in terms of fixed and random effects in multilevel data analyses. The author used examples at the local and national levels to ...

Hierarchical generalized linear modeling, also known as multilevel modeling, was used to adjust for individual-level confounders.

We adapt a semi-Bayesian hierarchical modeling framework to jointly characterize the space–time variability of seasonal precipitation totals and precipitation extremes across the Northern Great Plains ...

A novel Bayesian Hierarchical Network Model (BHNM) is designed for ensemble predictions of daily river stage, leveraging the spatial interdependence of river networks and hydrometeorological variables ...