Estimating and modelling bias of the hierarchical partitioning public-domain software: implications in environmental management and conservation.

ABSTRACT:

Background

Hierarchical partitioning (HP) is an analytical method of multiple regression that identifies the most likely causal factors while alleviating multicollinearity problems. Its use is increasing in ecology and conservation by its usefulness for complementing multiple regression analysis. A public-domain software "hier.part package" has been developed for running HP in R software. Its authors highlight a "minor rounding error" for hierarchies constructed from >9 variables, however potential bias by using this module has not yet been examined. Knowing this bias is pivotal because, for example, the ranking obtained in HP is being used as a criterion for establishing priorities of conservation.

Methodology/principal findings

Using numerical simulations and two real exam

SUBMITTER: Olea PP 

PROVIDER: S-EPMC2908144 | biostudies-literature | 2010 Jul

REPOSITORIES: biostudies-literature