On the application of multilevel modeling in environmental and ecological studies.
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.
Qian
Song S
SS
Nicholas School of the Environment, Duke University, Durham, North Carolina 27708, USA. song@duke.edu
Cuffney
Thomas F
TF
Alameddine
Ibrahim
I
McMahon
Gerard
G
Reckhow
Kenneth H
KH
D000383:Agriculture; D017753:Ecosystem; D004777:Environment; D008954:Models, Biological; D009609:Nitrous Oxide; D012987:Soil
D012987:Soil; D009609:Nitrous Oxide