sesem: Spatially Explicit Structural Equation Modeling

Structural equation modeling is a powerful statistical approach for the testing of networks of direct and indirect theoretical causal relationships in complex data sets with inter-correlated dependent and independent variables. Here we implement a simple method for spatially explicit structural equation modeling based on the analysis of variance co-variance matrices calculated across a range of lag distances. This method provides readily interpreted plots of the change in path coefficients across scale.

AuthorEric Lamb [aut, cre], Kerrie Mengersen [aut], Katherine Stewart [aut], Udayanga Attanayake [aut], Steven Siciliano [aut]
Date of publication2016-06-10 23:12:40
MaintainerEric Lamb <eric.lamb@usask.ca>
LicenseGPL (>= 2)
Version1.0.2
http://www.r-project.org, http://homepage.usask.ca/~egl388/index.html

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Files

sesem
sesem/inst
sesem/inst/CITATION
sesem/inst/NEWS.Rd
sesem/inst/doc
sesem/inst/doc/SESEM_examplescripts.r
sesem/NAMESPACE
sesem/data
sesem/data/truelove_results.rda
sesem/data/truelove_covar.rda
sesem/data/truelove.rda
sesem/data/plantcomp.rda
sesem/data/alexfiord.rda
sesem/R
sesem/R/sesem1.0.2.r
sesem/MD5
sesem/DESCRIPTION
sesem/man
sesem/man/truelove.Rd sesem/man/plotpath.Rd sesem/man/truelove_results.Rd sesem/man/avg.modindices.Rd sesem/man/truelove_covar.Rd sesem/man/bin.rsquare.Rd sesem/man/sesem-package.Rd sesem/man/plotmodelfit.Rd sesem/man/bin.results.Rd sesem/man/make.covar.Rd sesem/man/plantcomp.Rd sesem/man/gam.path.Rd sesem/man/alexfiord.Rd sesem/man/runModels.Rd sesem/man/make.bin.Rd sesem/man/modelsummary.Rd sesem/man/calc.dist.Rd sesem/man/plotbin.Rd

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