plot: Plot methods for various objects

Description Usage Arguments Note Author(s) References See Also Examples

Description

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

Usage

 1
 2
 3
 4
 5
 6
 7
 8
 9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
## 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, ...)

Arguments

x

An object returned from either a lavaan model class character, class 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 y1 and y2, 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 <[email protected]>

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

1
2
3
4
5
6
7
## Not run: 
## lavaan model
model <- "y ~ m + x
          m ~ x"
plot(model)

## End(Not run)

metaSEM documentation built on Oct. 18, 2018, 9:03 a.m.