%0 Journal Article
%A Shipley, B.
%T The AIC model selection method applied to path analytic models compared using a d-separation test
%B Ecology
%D 2013
%V 94
%P 560-564
%N 3
%X Classical path analysis is a statistical technique used to test causal
hypotheses involving multiple variables without latent variables,
assuming linearity, multivariate normality, and a sufficient sample
size. The d-separation (d-sep) test is a generalization of path analysis
that relaxes these assumptions. Although model selection using Akaike's
information criterion (AIC) is well established for classical path
analysis, this model selection technique has not yet been developed
for d-sep tests. In this paper, I explain how to use the AIC statistic
for d-sep tests, give a worked example, and include instructions
(supplemental material) to implement the analysis in the R computing
language. © 2013 by the Ecological Society of America.
%2 Export Date: 7 May 2013
Source: Scopus
CODEN: ECOLA
:doi 10.1890/12-0976.1
%( 00129658 (ISSN)
%K AIC statistic, D-separation (d-sep) test, Path analysis, Structural
equation modeling(SEM)
%# Luc
%Z timestamp=(2013.05.07)
%U http://www.scopus.com/inward/record.url?eid=2-s2.0-84876105687&partnerID=40&md5=cb2285ded15a8e792773ba49b90e2dfd
%F Shipley2013
%3 BibTeX type = ARTICLE