@ARTICLE {Shipley1997,
AUTHOR = {Shipley, B.},
TITLE = {Exploratory path analysis with applications in ecology and evolution},
JOURNAL = {American Naturalist},
YEAR = {1997},
VOLUME = {149},
PAGES = {1113-1138},
NUMBER = {6},
NOTE = {00030147 (ISSN) Cited By (since 1996): 39 Export Date: 26 April 2007
Source: Scopus CODEN: AMNTA doi: 10.1086/286041 Language of Original
Document: English Correspondence Address: Shipley, B.; Departement
de Biologie; Universite de Sherbrooke Sherbrooke, Que. J1K 2R1,
Canada; email: bshipley@courrier.usherb.ca References: Bentler,
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ABSTRACT = {In this article, I first describe some recent developments in the
identification of the structure of dependencies among variables
in multivariate data relevant to exploratory path analysis. I then
introduce a bootstrap modification of one important method (the
SGS algorithm) that is designed to improve error rates of exploratory
path analysis in the small data sets that are typical of studies
in ecology and evolution. Monte Carlo results indicate that this
modified technique can find path models that are close to the true
model even in very small data sets. The boot-strapped SGS algorithm
is then applied to a previously published data set involving attributes
affecting seed dispersal in St. Lucie's cherry.},
KEYWORDS = {exploratory path analysis multivariate analysis Prunus mahaleb Rosaceae},
OWNER = {brugerolles},
TIMESTAMP = {2007.12.05},
}