sesem (version 1.0.1)

plotpath: Function to plot spatial SEM results for individual paths

Description

A function to plot unstandardized path coefficients across lag distances. The default is to plot all directed paths with standard error bars, and greyed bars to indicate nonsignificant paths (z>0.05). A range of options are available to change the paths plotted, to add trendlines, and to alter the look of the plots.

Usage

plotpath(spatial_model_results, path.type = "directed", selectpath = "none selected",
	add.line = "none", add.error = T, pcut = 0.05, pch = 16, 
	lwd = 2, lty = 1,cex.main=1.2)

Arguments

spatial_model_results

a list object produced by function runModels

path.type

An option to select the paths to be plotted. "directed" = only directed paths plotted; "undirected" = only undirected correlations plotted; "both" = all paths plotted; "user" = allows user to specify particular paths and a particular order for plotting. A

selectpath

An option to select specific paths for plotting. Usage is as follows: selectpath==c(5,18,16,23,29) where values refer to path numbers. Path numbers can be obtained using spatial_model_results[[2]]

add.line

Options for plotting a fit line. "none" indicates no line; "step" plots straight line segments between points; "smooth" plots a smoothed curve fit using function lowess

add.error

Should standard error bars be added for each path coefficient

pcut

p-value cutoff above which points with non significant p-values are shaded grey. Set pcut=1 to have all points black.

pch

Selects plotting symbols

lwd

Sets trendline width

lty

Sets trendline format

cex.main

Sets plot title font

References

Lamb, E. G., K. Mengersen, K. J. Stewart, U. Attanayake, and S. D. Siciliano. Submitted. Spatially explicit structural equation modeling. Ecology. Rosseel, Y. 2012 lavaan: an R package for structural equation modeling. Journal of Statistical Software 48:1-36.

See Also

sem, make.covar, runModels, modelsummary, plotmodelfit, gam.path

Examples

#data=truelove
#distancematrix<-calc.dist(truelove)
#Truelove_bins<-make.bin(distancematrix,type="ALL",p.dist=20)
#binsize<-Truelove_bins[1][[1]] #truelove lowland bin sizes
#binname<-Truelove_bins[2][[1]] #truelove lowland bin names

#covariances<-make.covar(truelove,distancematrix,binsize,binname)
#covariances

# path model for the truelove dataset
#spatial_model<-'
#	Gram ~ Moisture
#	N_Fix ~ Bryoph + Lich + SoilCrust
#	SoilCrust ~ Bryoph + Lich + Gram + Shrubs + Forbs	
#	Bryoph ~ Gram + Shrubs + Forbs + Moisture
#	Lich ~ Moisture + Forbs + Gram + Shrubs + Bryoph
#	Forbs ~ Moisture
#	Gram ~~ Forbs
#	Shrubs ~ Moisture	
#	Gram ~~ Shrubs
#	Shrubs ~~ Forbs
#	'
#
#results<-runModels(spatial_model,covariances)

#The above script produces the sesem object stored as truelove_results

data=truelove_results

plotpath(truelove_results)
truelove_results[[2]]# list of path names
plotpath(truelove_results,path.type="user",selectpath=c(5,7,8))