title: On the application of multilevel modeling in environmental and ecological studies.
abstract: This paper illustrates the advantages of a multilevel/hierarchical approach for predictive modeling, including flexibility of model formulation, explicitly accounting for hierarchical structure in the data, and the ability to predict the outcome of new cases. As a generalization of the classical approach, the multilevel modeling approach explicitly models the hierarchical structure in the data by considering both the within- and between-group variances leading to a partial pooling of data across all levels in the hierarchy. The modeling framework provides means for incorporating variables at different spatiotemporal scales. The examples used in this paper illustrate the iterative process of model fitting and evaluation, a process that can lead to improved understanding of the system being studied.
authors.affiliation: Nicholas School of the Environment, Duke University, Durham, North Carolina 27708, USA. song@duke.edu
authors.forename: Song S
authors.initials: SS
authors.lastname: Qian
authors.forename: Thomas F
authors.initials: TF
authors.lastname: Cuffney
authors.forename: Ibrahim
authors.initials: I
authors.lastname: Alameddine
authors.forename: Gerard
authors.initials: G
authors.lastname: McMahon
authors.forename: Kenneth H
authors.initials: KH
authors.lastname: Reckhow
mesh_terms: D000383:Agriculture; D017753:Ecosystem; D004777:Environment; D008954:Models, Biological; D009609:Nitrous Oxide; D012987:Soil
chemical_list: D012987:Soil; D009609:Nitrous Oxide