plot: Plot methods for various objects

In metaSEM: Meta-Analysis using Structural Equation Modeling

Plot methods for various objects

Description

It plots the models from either the lavaan model or meta, wls, and osmasem objects.

Usage

## S3 method for class 'meta'
plot(x, effect.sizes, add.margin = 0.1, interval = 0.95,
     main= "Effect Sizes and their Confidence Ellipses",
     axis.labels= paste("Effect size ", effect.sizes, sep = ""),
     study.col = "black", study.pch = 19, study.min.cex = 0.8,
     study.weight.plot = FALSE, study.ellipse.plot = TRUE,
     study.ellipse.col = "black", study.ellipse.lty = 2,
     study.ellipse.lwd = 0.5, estimate.col = "blue",
     estimate.pch = 18, estimate.cex = 2,
     estimate.ellipse.plot = TRUE, estimate.ellipse.col = "red",
     estimate.ellipse.lty = 1, estimate.ellipse.lwd = 2,
     randeff.ellipse.plot = TRUE, randeff.ellipse.col = "green",
     randeff.ellipse.lty = 1, randeff.ellipse.lwd = 2,
     univariate.plot = TRUE, univariate.lines.col = "gray",
     univariate.lines.lty = 3, univariate.lines.lwd = 1,
     univariate.polygon.width = 0.02,
     univariate.polygon.col = "red",
     univariate.arrows.col = "green", univariate.arrows.lwd = 2,
     diag.panel = FALSE, xlim=NULL, ylim=NULL, ...)
## S3 method for class 'character'
plot(x, fixed.x=FALSE, nCharNodes=0, nCharEdges=0,
     layout=c("tree", "circle", "spring", "tree2", "circle2"),
     sizeMan=8, sizeLat=8, edge.label.cex=1.3, color="white", ...)
## S3 method for class 'wls'
plot(x, manNames=NULL, latNames=NULL, labels=c("labels", "RAM"),
     what="est", nCharNodes=0, nCharEdges=0,
     layout=c("tree", "circle", "spring", "tree2", "circle2"),
     sizeMan=8, sizeLat=8, edge.label.cex=1.3, color="white",
     weighted=FALSE, ...)
## S3 method for class 'osmasem'
plot(x, manNames=NULL, latNames=NULL, labels=c("labels", "RAM"),
     what="est", nCharNodes=0, nCharEdges=0,
     layout=c("tree", "circle", "spring", "tree2", "circle2"),
     sizeMan=8, sizeLat=8, edge.label.cex=1.3, color="white",
  weighted=FALSE, ...)
## S3 method for class 'osmasem2'
plot(x, manNames=NULL, latNames=NULL, labels=c("labels", "RAM"),
     what="est", nCharNodes=0, nCharEdges=0,
     layout=c("tree", "circle", "spring", "tree2", "circle2"),
     sizeMan=8, sizeLat=8, edge.label.cex=1.3, color="white",
  weighted=FALSE, ...)
## S3 method for class 'mxsem'
plot(x, manNames=NULL, latNames=NULL, labels=c("labels", "RAM"),
     what="est", nCharNodes=0, nCharEdges=0,
     layout=c("tree", "circle", "spring", "tree2", "circle2"),
     sizeMan=8, sizeLat=8, edge.label.cex=1.3, color="white",
    weighted=FALSE, ...)

Arguments

x	An object returned from either a lavaan model class character, osmasem, osmasem3L, wls or meta
effect.sizes	Numeric values indicating which effect sizes to be plotted. At least two effect sizes are required. To plot the effect sizes of y_1 and y_2, one may use effect.sizes=c(1,2). If it is missing, all effect sizes will be plotted in a pairwise way.
add.margin	Value for additional margins on the left and bottom margins.
interval	Interval for the confidence ellipses.
main	Main title of each plot. If there are multiple plots, a vector of character titles may be used.
axis.labels	Labels for the effect sizes.
study.col	The color for individual studies. See col in par.
study.pch	Plotting character of individual studies. See pch in points.
study.min.cex	The minimum value of cex for individual studies. See cex in par.
study.weight.plot	Logical. If TRUE, the plotting size of individual studies (cex) will be proportional to one over the square root of the determinant of the sampling covariance matrix of the study.
study.ellipse.plot	Logical. If TRUE, the confidence ellipses of individual studies are plotted.
study.ellipse.col	The color of the confidence ellipses of individual studies. See col in par.
study.ellipse.lty	The line type of the confidence ellipse of individual studies. See lty in par.
study.ellipse.lwd	The line width of the confidence ellipse of individual studies. See lwd in par.
estimate.col	The color of the estimated effect size. See col in par.
estimate.pch	Plotting character of the estimated effect sizes. See pch in points.
estimate.cex	The amount of plotting of the estimated effect sizes. See cex in par.
estimate.ellipse.plot	Logical. If TRUE, the confidence ellipse of the estimated effect sizes will be plotted.
estimate.ellipse.col	The color of the confidence ellipse of the estimated effect sizes. See col in par.
estimate.ellipse.lty	The line type of the confidence ellipse of the estimated effect sizes. See lty in par.
estimate.ellipse.lwd	The line width of the confidence ellipse of the estimated effect sizes. See lwd in par.
randeff.ellipse.plot	Logical. If TRUE, the confidence ellipses of the random effects will be plotted.
randeff.ellipse.col	Color of the confidence ellipses of the random effects. See col in par.
randeff.ellipse.lty	The line type of the confidence ellipses of the random effects. See lty in par.
randeff.ellipse.lwd	The line width of the confidence ellipses of the random effects. See lwd in par.
univariate.plot	Logical. If TRUE, the estimated univariate effect sizes will be plotted.
univariate.lines.col	The color of the estimated univariate effect sizes. See col in par.
univariate.lines.lty	The line type of the estimated univariate effect sizes. See lty in par.
univariate.lines.lwd	The line width of the estimated univariate effect sizes. See lwd in par.
univariate.polygon.width	The width of the polygon of the estimated univariate effect sizes.
univariate.polygon.col	The color of the polygon of the estimated univariate effect sizes.
univariate.arrows.col	The color of the arrows of the estimated univariate effect sizes.
univariate.arrows.lwd	The line width of the arrows of the estimated univariate effect sizes.
diag.panel	Logical. If TRUE, diagonal panels will be created. They can then be used for forrest plots for univariate meta-analysis.
xlim	NULL or a numeric vector of length 2; if it is NULL, it provides defaults estimated from the data.
ylim	NULL or a numeric vector of length 2; if it is NULL, it provides defaults estimated from the data.
fixed.x	Argument passed to semPlotModel.
manNames	Argument passed to semPaths
latNames	Argument passed to semPaths
labels	Argument passed to semPaths
what	Argument passed to semPaths
nCharNodes	Argument passed to semPaths
nCharEdges	Argument passed to semPaths
layout	Argument passed to semPaths
color	Argument passed to semPaths
sizeMan	Argument passed to semPaths
sizeLat	Argument passed to semPaths
edge.label.cex	Argument passed to semPaths
weighted	Argument passed to semPaths
...	Further arguments passed to the methods.

Note

The estimated effect sizes and random effects are based on the labels Intercept1, Intercept2, ... and Tau2_1_1, Tau2_2_1, Tau2_2_2, etc. At least two effect sizes are required for this function.

Author(s)

Mike W.-L. Cheung <[e-mail]>

References

Cheung, M. W.-L. (2013). Multivariate meta-analysis as structural equation models. Structural Equation Modeling, 20, 429-454.

See Also

Berkey98, wvs94a meta2semPlot semPaths

Examples

## lavaan model
model <- "y ~ m + x
          m ~ x"
plot(model)

metaSEM documentation built on Sept. 30, 2024, 9:21 a.m.