qgraph {qgraph}R Documentation



This is the main function of qgraph. It is typically used to visualize the relationship between several variables as a network. This function can be used to create various types of networks based on a number of input options. Please see the details section for more detail.


qgraph( input, ... )



Can be either a weights matrix or an edgelist. Can also be an object of class "sem" (sem), "mod" (sem), "lavaan" (lavaan), "principal" (psych), "loadings" (stats), "factanal" (stats), "graphNEL" (Rgraphviz) or "pcAlgo" (pcalg)


Any additional arguments described below. Also a list with class "qgraph" can be added that contains any of these arguments (this is returned invisibly by the function)


The qgraph function has a lot of arguments. Mostly the default values of these work well. Because of the amount of arguments the usage of the qgraph function has been reduced by using the ... method for clarity. This does mean that arguments need to be specified by using their exact name. For instance, to specify color="red" you can not use col="red".

Below is a complete list of all the arguments that can be used in qgraph and a detailed guide on how the function can be used.


qgraph returns (invisibly) a 'qgraph' object that contains all the arguments used, with the exception of the 'layout' argument which is set to the final layout used in the graph. This can then be sent to a new qgraph function to use the same arguments in the new plot.

One of the values returned is 'layout.orig', the original (not rescaled) layout, which needs to be used when using constraint layouts.

Important additional arguments


Logical, calls qgraph.gui if TRUE to open GUI window.


This argument controls the layout of the graph. "circle" places all nodes in a single circle, "circular" gives a circular layout in which each group is put in separate circles and "spring" gives a force embedded layout. It also can be a matrix with a row for each node and x and y coordinates in the first and second column respectively. Defaults to "circular" in weighted graphs without a groups list, "groups" in weighted graphs with a groups list, and "spring" in unweighted graphs. Can also be a function from the igraph package.


An object that indicates which nodes belong together. Can be a list in which each element is a vector of integers identifying the numbers of the nodes that belong together, or a factor.


Edges with absolute weights under this value are omitted. Defaults to 0 for graphs with less than 50 nodes or 0.1 for larger graphs.


qgraph regards the highest of the maximum or highest absolute edge weight as the highest weight to scale the edge widths too. To compare several graphs, set this argument to a higher value than any edge weight in the graphs (typically 1 for correlations).


In weighted graphs, this argument can be used to cut the scaling of edges in width and color saturation. Edges with absolute weights over this value will have the strongest color intensity and become wider the stronger they are, and edges with absolute weights under this value will have the smallest width and become vaguer the weaker the weight. If this is set to NULL, no cutoff is used and all edges vary in width and color. Defaults to NULL for graphs with less then 50 nodes and 0.3 to larger graphs.


Logical indicating if minimum, maximum and cutoff score should be printed under the graph. Defaults to FALSE.

Output arguments


A vector of the form c(bottom, left, top, right) which gives the margins. Works similar to the argument in par(). Defaults to c(3,3,3,3)


A character containing the file type to save the output in. "R" and "x11" outputs in a new R window ("x11" is preferred for Rstudio), "pdf" creates a pdf file. "svg" creates a svg file (requires RSVGTipsDevice). "tex" creates LaTeX code for the graph (requires tikzDevice). 'jpg', 'tiff' and 'png' can also be used. If this is given any other string (e.g. filetype="") no device is opened. Defaults to 'R' if the current device is the NULL-device or no new device if there already is an open device.


Name of the file without extension


Width of the plot, in inches


Height of the plot, in inches


Logical, should the plot be normalized to the plot size. If TRUE (default) border width, vertex size, edge width and arrow sizes are adjusted to look the same for all sizes of the plot, corresponding to what they would look in a 7 by 7 inches plot if normalize is FALSE.


Logical. If filetype="tex" this argument can be used to choose between making the output a standalone LaTeX file or only the codes to include the graph.

Graphical arguments


A vector with a color for each element in the groups list, or a color for each node. Defaults to the background color ("bg" argument, which defaults to "white") without groups list and rainbow(length(groups)) with a groups list.


Logical value indicating if a legend should be plotted. Defaults to TRUE if a groups object is supplied


Scalar of the legend. defaults to 1


Relative size of the graph compared to the layout. Defaults to 2.5


A value indicating the size of the nodes (horizontal if shape is "rectangle". Can also be a vector of length 2 (nodes are scaled to degree) or a size for each node. Defaults to: max((-1/72)*(nNodes)+5.35,1)


A value indicating the vertical size of the nodes where the shape is "rectangle". Can also be a vector of length 2 (nodes are scaled to degree) or a size for each node. Defaults to the value of 'vsize'. If 'vsize' is not assigned this value is used as a scalar to 'vsize' (e.g., vsize2 = 1/2 would result in rectangled nodes where the height is half the default width)


Size of the largest edge (or what it would be if there was an edge with weight maximum). Defaults to: max((-1/72)*(nNodes)+5.35,1) for weighted graphs and 2 for unweighted graphs. In directed graphs these values are halved.


If FALSE, no labels are plotted. If TRUE, order in weights matrix is used as labels. This can also be a vector with a label for each node. Defaults for graphs with less than 20 nodes to a 3 character abbreviation of the columnames and rownames if these are identical or else to TRUE. If a label contains an asterisk (e.g. "x1*") then the asterisk will be omitted and the label will be printed in symbol font (use this for Greek letters)


Scalar on the label size.


Controls the proportion of the width of the node that the label rescales to. Defaults to 0. 9.


A single string that is used to normalize label size. If the width of the label is lower than the width of the hypothetical label given by this argument the width of label given by this argument is used instead. Defaults to "OOO" so that every label up to three characters has the same fontsize.


Logical indicating if labels should be scaled to fit the node. Defaults to TRUE.


If FALSE, no edge labels are plotted. If TRUE, numerical edge weights are printed on the edges. This can also be a vector with a label for each edge. Defaults to FALSE. If a label contains an asterisk (e.g. "y1*") then the asterisk will be omitted and the label will be printed in symbol font (use this for Greek letters)


Either a single number or a number per edge used as a scalar of the edge label size. Defaults to 1.


Either a logical or character vector/matrix. Indicates the background behind edge labels. If TRUE (default) a white background is plotted behind each edge label. If FALSE no background is plotted behind edge labels. Can also be a single color character, a vector or matrix of color vectors for each edge.


If this is TRUE, a background is plotted in which node colors cast a light of that color on a black background. Can also be a character containing the color of the background Defaults to FALSE


The higher this is, the less light each node gives if bg=TRUE. Defaults to 6.


square root of the number of pixels used in bg=TRUE, defaults to 100.


In weighted graphs: logical indicating if the edges should fade to white (FALSE) or become more transparent (TRUE; use this only if you use a background). In directed graphs this is a value between 0 and 1 indicating the level of transparency. (also used as 'transparency')


if TRUE (default) and if 'edge.color' is assigned, transparency will be added to edges that are not transparent (or for which no transparency has been assigned) relative to the edge strength, similar if 'trans' is set to TRUE.


Color of positive edges. Can be a vector of two to indicate color of edges under 'cut' value and color of edges over 'cut' value. If 'fade is set to TRUE the first color will be faded the weaker the edge weight is. If this is only one element this color will also be used for edges stronger than the 'cut' value. Defaults to c("#009900","darkgreen")


Color of negative edges. Can be a vector of two to indicate color of edges under 'cut' value and color of edges over 'cut' value. If 'fade is set to TRUE the first color will be faded the weaker the edge weight is. If this is only one element this color will also be used for edges stronger than the 'cut' value. Defaults to c("#BF0000","red")


Color to indicate the default edge color of unweighted graphs. Defaults to "#808080".


Exponent of transformation in color intensity of relative strength. Defaults to 1 for linear behavior.


Character containing the color of the labels, defaults to "black"


Should the diagonal also be plotted as edges? defaults to FALSE. Can also be "col" to plot diagonal values as vertex colors.


If diag=T, this can be used to scale the size of the loop. defaults to 1.


Line type, see 'par'


See 'par'


Logical indicating if borders should be plotted, defaults to TRUE.


Color vector indicating colors of the borders. Is repeated if length is equal to 1. Defaults to "black"


Controls the width of the border. Defaults to 2 and is comparable to 'lwd' argument in 'points'.


A character containing the shape of the nodes. "circle", "square", "triangle" and "diamond" are supported. Can also be a vector with a shape for each node. Defaults to "circle".


Logical, set to TRUE to plot the graph in grayscale colors


A vector with tooltips for each node, only used when filetype='svg' or filetype='tex'


Transparency of the nodes, must be an integer between 0 and 255, 255 indicating no transparency. Defaults to 255


Logical, should a Venn-diagram like overlay be plotted? If TRUE then for each group a x% confidence region is plotted for the X and Y position, using ellipse


Specifies the size of the overlay ellipses. Corresponds to the confidence level (default is 0.5)


A vector that can be used to rotate the circles created with the circular layout. Must contain the rotation in radian for each group of nodes. Defaults to zero for each group.


A list of arguments passed to qgraph.layout.fruchtermanreingold when layout="spring" or to an igraph function when such a function is assigned to 'layout'


A scalar on the size of the circles created with the circular layout.


Should the original aspect ratio be maintained if rescale = TRUE? Defaults to FALSE. Set this to TRUE to keep the aspect ratio of the original layout (e.g. result from layout="spring"). Currently this only works correctly if the plotting area is square. This can be forced with exporting the graph using 'height', 'width' and 'filetype' arguments.


A list with as elements R expressions or NULL for each node. If it is an R expression it is evaluated to create a plot for the node.


A character vector of length 1 or the same length as the number of nodes indicating the file location of PNG or JPEG images to use as nodes. Can be NA to not plot an image as node and overwrites 'subplots'

Additional arguments for directed graphs


Logical indicating if edges are directed or not. Can be TRUE or FALSE to indicate if all edges are directed, a logical vector (when using edgelists) or a logical matrix (when using weights matrix)


A value indicating how strongly edges should be curved. Either a single value, a vector (edgelist input) with a value for each edge or a matrix (weights matrix input). NA indicates default curve behavior should be used, which only curves edges if there are multiple edges between two nodes.


Logical, indicating if all edges should be curved with the value of the 'curve' or only edges between nodes that have share multiple edges.


The default curvature. Defaults to 1.


A logical indicating if arrows should be drawn, or a number indicating how much arrows should be drawn on each edge. If this is TRUE, a simple arrow is plotted, if this is a number, arrows are put in the middle of the edges.


Angle of the arrowhead, in radians. Defaults to pi/8 for unweighted graphs and pi/4 for weighted graphs.


Size of the arrowhead.


Logical indicating if open (TRUE) or closed (FALSE) arrowheads should be drawn.


If this is TRUE, Then directional edges between nodes that have two edges between them are not curved. Defaults to FALSE. Can also be a logical vector (when using edgelists) or a logical matrix (when using weights matrix)

Arguments for graphs based on significance values


This argument defines the mode used for coloring the edges. The default, "strength" assumes each edge weight indicates the strength of connection centered around and makes positive edges green and negative edges red. If this is set to "sig" then the edge weights are assumed to be significance values and colored accordingly. This can also include negative values, which will be interpreted as p-values based on negative statistics.


A vector of max 4 elements indicating the alpha level cutoffs. Defaults to c(0.0001,0.001,0.01,0.05)


Logical indicating if edge weights with a p-value over the highest alpha level should be omitted. Defaults to FALSE, can be used with any mode


The function used to scale the edges if mode="sig". Defaults to $function(x)0.8*(1-x)^(log(0.4/0.8,1-0.05))$


Logical indicating if a bonferonni correction should be applied if mode="sig". If so p-values are multiplied by the number of edges

Additional options for Correlation Matrices


Type of graph to be made, for use with a correlation matrix as input. "association" will plot the matrix as is, "concentration" will first compute partial correlations between each pair of nodes (controlled for all other variables) and "factorial" will create a graph based on an exploratory factor analysis. Finally "sig" will transform all correlations in p-values (using the fdrtool package; Korbinian Strimmer, 2009) and force mode="sig". "sig2" will do the same but show p-values based on negative statistics in shades of orange

Arguments for plotting scores on nodes


This argument can be used to plot scores of an individual on the test. Should be a vector with the scores for each item. Currently this can only be integer values (e.g.\ LIKERT scales).


Vector of length two indicating the range of the scores, if scores is assigned.

Arguments for manually defining graphs


The mode argument (see section on significance graph arguments) can also be used to make the weights matrix correspond directly to the width of the edges (as in lwd of plot()). To do this, set mode to "direct".


This argument can be used to overwrite the colors. Can be either a single value to make all edges the same color, a matrix with a color for each edge (when using a weights matrix) or a vector with a color for each edge (when using an edgelist). NA indicates that the default color should be used.

Arguments for knots (tying together edges)


This argument can be used to tie edges together in their center, which can be useful to, for example, indicate interaction effects. This argument can be assigned a list where each element is a vector containing the edge numbers that should be knotted together. Another option is to assign the argument a integer vector (for edgelists) or a matrix (for weight matrices) with 0 indicating edges that should not be tied together, and increasing numbers indicating each knot.


The size of the knots. Can be of length one or a vector with the size of each knot. Similar to 'vsize'. Defaults to 1.


The color of the knots. Can be of length one or a vector with the size of each knot. Defaults to NA, which will result in a mix of the knotted edge colors.


Logical indicating if a border should be plotted around the knot. Can be of length one or a vector with the size of each knot. Works similar to 'borders'. Defaults to FALSE


Color of the knot borders. Can be of length one or a vector with the size of each knot. Works similar to 'border.color'. Defaults to "black"


Width of the knot borders. Can be of length one or a vector with the size of each knot. Works similar to 'border.width'. Defaults to 1

Additional arguments


Logical, if TRUE 'input' is assumed to be an edgelist, else if FALSE input is assumed to be a weights matrix. By default this is chosen automatically based on the dimensions of 'input' and this argument is only needed if the dimensions are ambiguous (square matrix with 2 or 3 rows/columns)


Logical that can be used to force either a weighted graph (TRUE) or an unweighted graph(FALSE).


The number of nodes, only needs to be specified if the first argument is an edge-list and some nodes have no edges


Runs qgraph but does not plot. Useful for saving the output (i.e. layout) without plotting


Logical. Should a new plot be made? Defaults to TRUE. Set to FALSE to add the graph to the existing plot.


Logical. Defines if the layout should be rescaled to fit the -1 to 1 x and y area. Defaults to TRUE. Can best be used in combination with plot=FALSE.


A vector with a scalar for respectively the x and y coordinates of the layout (which default plotting area is from -1 to 1 on both x and y axis). Setting this to e.g. c(2,2) would make the plot twice as big. Use this in combination with 'layoutOffset' and 'plot' arguments to define the graph placement on an existing plot.


A vector with the offset to the x and coordinates of the center of the graph (defaults to (0,0)). Use this in combination with 'layoutScale' and 'plot' arguments to define the graph placement on an existing plot.

Using qgraph to plot graphs

The first argument of qgraph(), 'input', is the input. This can be a number of objects but is mainly either a weights matrix or an edgelist. Here we will assume a graph is made of n nodes connected by m edges. qgraph is mainly aimed at visualizing (statistical) relationships between variables as weighted edges. In these edge weights a zero indicates no connection and negative values are comparable in strength to positive values. Many (standardized) statistics follow these rules, the most important example being correlations. In the special case where all edge weights are either 0 or 1 the weights matrix is interpreted as an adjacency matrix and an unweighted graph is made.

a weights matrix is a square n by n matrix in which each row and column represents a node. The element at row i and column j indicates the connection from node i to node j. If the weights matrix is symmetrical an undirected graph is made and if the matrix is asymmetrical a directed graph is made (note that due to floating point errors seemingly symmetrical matrices may actually be asymmetrical). These matrices occur naturally in statistics or can easily be obtained through matrix algebra, the most important example being correlation matrices.

An edgelist can also be used. This is a m by 2 matrix (not a list!) in which each row indicates an edge. The first column indicates the number of the start of the edge and the second column indicates the number of the end of the edge. The number of each node is a unique integer between 1 and n. The total number of nodes will be estimated by taking the highest value of the edgelist. If this is incorrect (there are nodes with no edges beyond the ones already specified) the 'nNodes' argument can be used. If an integer between 1 and n is missing in the edgelist it is assumed to be a node with no edges. To create a weighted graph edge weights can be added as a third column in the edgelist. By default using an edgelist creates a directed graph, but this can be set with the 'directed' argument.

Interpreting graphs

In weighted graphs green edges indicate positive weights and red edges indicate negative weights. The color saturation and the width of the edges corresponds to the absolute weight and scale relative to the strongest weight in the graph. It is possible to set this strongest edge by using the 'maximum' argument. When 'maximum' is set to a value above any absolute weight in the graph that value is considered the strongest edge (this must be done to compare different graphs; a good value for correlations is 1). Edges with an absolute value under the 'minimum' argument are omitted (useful to keep filesizes from inflating in very large graphs).

In larger graphs the above edge settings can become hard to interpret. With the 'cut' argument a cutoff value can be set which splits scaling of color and width. This makes the graphs much easier to interpret as you can see important edges and general trends in the same picture. Edges with absolute weights under the cutoff score will have the smallest width and become more colorful as they approach the cutoff score, and edges with absolute weights over the cutoff score will be full red or green and become wider the stronger they are.

Specifying the layout

The placement of the nodes (i.e. the layout) is specified with the 'layout' argument. It can be manually specified by entering a matrix for this argument. The matrix must have a row for each node and two columns indicating its X and Y coordinate respectively. qgraph plots the nodes on a (-1:1)(-1:1) plane, and the given coordinates will be rescaled to fit this plane unless 'rescale' is FALSE (not recommended). Another option to manually specify the layout is by entering a matrix with more then two columns. This matrix must then consist of zeroes and a number (the order in the weights matrix) for each node indicating it's place. For example:

0 0 2 0 0

1 0 3 0 4

will place node 2 at the top in the center, node 1 at the bottom left corner, node 3 at the bottom in the center and node 4 at the bottom right corner. It is recommended however that one of the integrated layouts is used. 'layout' can be given a character as argument to accomplish that. layout="circular" will simply place all nodes in a circle if the groups argument is not used and in separate circles per group if the groups argument is used (see next section).

The circular layout is convenient to see how well the data conforms to a model, but to show how the data clusters another layout is more appropriate. By specifying layout="spring" the Fruchterman-reingold algorithm (Fruchterman & Reingold, 1991), which has been ported from the SNA package (Butts, 2010), can be used to create a force-directed layout. In principle, what this function does is that each node (connected and unconnected) repulse each other, and connected nodes also attract each other. Then after a number of iterations (500 by default) in which the maximum displacement of each node becomes smaller a layout is achieved in which the distance between nodes correspond very well to the absolute edge weight between those nodes.

A solution to use this function for weighted graphs has been taken from the igraph package (Csardi G & Nepusz T, 2006) in which the same function was ported from the SNA package. New in qgraph are the option to include constraints on the nodes by fixing a coordinate for nodes or reducing the maximum allowed displacement per node. This can be done with the 'layout.par' argument. For more information see qgraph.layout.fruchtermanreingold.

By default, 'layout' is set to "spring" for unweighted and directed graphs and "circular" otherwise.

Specifying a measurement model

A measurement model can be specified with the 'groups' argument. This must be a list in which each element is a vector containing the numbers of nodes that belong together (numbers are taken from the order in the weights matrix). All numbers must be included. If a groups list is specified the "groups" layout can be used to place these nodes together, the nodes in each group will be given a color, and a legend can be plotted (by setting 'legend' to TRUE). The colors will be taken from the 'color' argument, or be generated with the rainbow function.


By default qgraph will plot the graph in a new R window. However the graphs are optimized to be plotted in a PDF file. To easily create a pdf file set the 'filetype' argument to "pdf". 'filename' can be used to specify the filename and folder to output in. 'height' and 'width' can be used to specify the height and width of the image in inches. By default a new R window is opened if the current device is the NULL-device, otherwise the current device is used (note that when doing this 'width' and 'height' still optimize the image for those widths and heights, even though the output screen size isn't affected, this is especially important for directed graphs!).

Furthermore filetype can also be set to numerous other values. Alternatively any output device in R can be used by simply opening the device before calling qgraph and closing it with dev.off() after calling qgraph.

The graphs can also be outputted in an SVG file using the RSVGTipsDevice package (Plate, 2009). An SVG image can be opened in most browsers (firefox and chrome are recommended), and can be used to display tooltips. Each node can be given a tooltip with the 'tooltips' argument. The function qgraph.svg can be used to make a battery of svg pictures with hyperlinks to each other, working like a navigation menu.

IMPORTANT NOTE: RSVGTipsDevice is a 32-bit only package, so SVG functionality is not available in 64bit versions of R.

Finally, the filetype 'tex' can be used. This uses the tikzDevice package to create a LaTeX file that can then be compiled in your LaTeX compiler to create a pdf file. The main benefit of this over plotting directly in a pdf file is that tooltips can be added which can be viewed in several PDF document readers (Adobe Reader is recommended for the best result).

Manual specification of color and width

In qgraph the widths and colors of each edge can also be manually controlled. To directly specify the width of each edge set the 'mode” argument to "direct". This will then use the absolute edge weights as the width of each edge (negative values can still be used to make red edges). To manually set the color of each edge, set the 'edge.color' argument to a matrix with colors for each edge (when using a weights matrix) or a vector with a color for each edge (when using an edgelist).

Additional information

By default, edges will be straight between two nodes unless there are two edges between two nodes. To overwrite this the 'bidirectional' argument can be set to TRUE, which will turn two edges between two nodes into one bidirectional edge. 'bidirectional' can also be a vector with TRUE or FALSE for each edge.

To specify the strength of the curve the argument 'curve' can be used (but only in directional graphs). 'curve' must be given a numerical value that represent an offset from the middle of the straight edge through where the curved edge must be drawn. 0 indicates no curve, and any other value indicates a curve of that strength. A value of 0.3 is recommended for nice curves. This can be either one number or a vector with the curve of each edge.

Nodes and edges can be given labels with the 'labels' and the 'edge.labels' arguments. 'labels' can be set to FALSE to omit labels, TRUE (default) to set labels equal to the node number (order in the weights matrix) or it can be a vector with the label for each node. Edge labels can also be set to FALSE to be omitted (default). If 'edge.labels' is TRUE then the weight of each label is printed. Finally, 'edge.labels' can also be a vector with the label for each edge. If a label (both for edges and nodes) contain an asterisk then the asterisk is omitted and that label is printed in the symbol font (useful to print Greek letters).

A final two things to try: the 'scores' argument can be given a vector with the scores of a person on each variable, which will then be shown using colors of the nodes, And the 'bg' argument can be used to change the background of the graph to another color, or use bg=TRUE for a special background (do set transparency=TRUE when using background colors other then white).


If this function crashes for any reason with the filetype argument specified, run:


To shut down the output device!


Sacha Epskamp <qgraph@sachaepskamp.com>


Sacha Epskamp, Angelique O. J. Cramer, Lourens J. Waldorp, Verena D. Schmittmann, Denny Borsboom (2012). qgraph: Network Visualizations of Relationships in Psychometric Data. Journal of Statistical Software, 48(4), 1-18. URL http://www.jstatsoft.org/v48/i04/.

Carter T. Butts <buttsc@uci.edu> (2010). sna: Tools for Social Network Analysis. R package version 2.2-0. http://CRAN.R-project.org/package=sna

Csardi G, Nepusz T (2006). The igraph software package for complex network research, InterJournal, Complex Systems 1695. http://igraph.sf.net

Korbinian Strimmer (2009). fdrtool: Estimation and Control of (Local) False Discovery Rates. R package version 1.2.6. http://CRAN.R-project.org/package=fdrtool

Plate, T. <tplate@acm.org> and based on RSvgDevice by T Jake Luciani <jakeluciani@yahoo.com> (2009). RSVGTipsDevice: An R SVG graphics device with dynamic tips and hyperlinks. R package version 1.0-1.

Fruchterman, T. & Reingold, E. (1991). Graph drawing by force-directed placement. Software - Pract. Exp. 21, 1129?1164.

See Also

qgraph qgraph.gui qgraph.animate qgraph.efa qgraph.pca qgraph.loadings qgraph.sem qgraph.lavaan qgraph.cfa qgraph.svg qgraph.panel


### BIG 5 DATASET ###
# Load big5 dataset:

# Correlations:
Q <- qgraph(cor(big5),minimum=0.25,cut=0.4,vsize=1.5,groups=big5groups,legend=TRUE,borders=FALSE)
title("Big 5 correlations",line=2.5)

plot of chunk unnamed-chunk-1

## Not run: 
##D # Same graph with spring layout:
##D Q <- qgraph(Q,layout="spring")
##D title("Big 5 correlations",line=2.5)
##D # Same graph with Venn diagram overlay:
##D qgraph(Q,overlay=TRUE)
##D title("Big 5 correlations",line=2.5)
##D # Same graph with different color scheme:
##D qgraph(Q,posCol="blue",negCol="purple")
##D title("Big 5 correlations",line=2.5)
##D # Significance graph (circular):
##D qgraph(Q,graph="sig",layout="circular")
##D title("Big 5 correlations (p-values)",line=2.5)
##D # Significance graph:
##D qgraph(Q,graph="sig")
##D title("Big 5 correlations (p-values)",line=2.5)
##D # Significance graph (distinguishing positive and negative statistics):
##D qgraph(Q,graph="sig2")
##D title("Big 5 correlations (p-values)",line=2.5)
##D # Grayscale graphs:
##D qgraph(Q,gray=TRUE,layout="circular")
##D title("Big 5 correlations",line=2.5)
##D qgraph(Q,graph="sig",gray=TRUE)
##D title("Big 5 correlations (p-values)",line=2.5)
##D # Correlations graph with scores of random subject:
##D qgraph(cor(big5),minimum=0.25,cut=0.4,vsize=1.5,groups=big5groups,legend=TRUE,borders=FALSE,scores=as.integer(big5[sample(1:500,1),]),scores.range=c(1,5))
##D title("Test scores of random subject",line=2.5)
##D layout(1)
##D # EFA:
##D big5efa <- factanal(big5,factors=5,rotation="promax",scores="regression")
##D qgraph(big5efa,groups=big5groups,layout="circle",rotation="promax",minimum=0.2,cut=0.4,vsize=c(1.5,15),borders=FALSE,vTrans=200)
##D title("Big 5 EFA",line=2.5)
##D # PCA:
##D library("psych")
##D big5pca <- principal(cor(big5),5,rotate="promax")
##D qgraph(big5pca,groups=big5groups,layout="circle",rotation="promax",minimum=0.2,cut=0.4,vsize=c(1.5,15),borders=FALSE,vTrans=200)
##D title("Big 5 PCA",line=2.5)
##D set.seed(1)
##D adj=matrix(sample(0:1,10^2,TRUE,prob=c(0.8,0.2)),nrow=10,ncol=10)
##D qgraph(adj)
##D title("Unweighted and directed graphs",line=2.5)
##D # Save plot to nonsquare pdf file:
##D qgraph(adj,filetype='pdf',height=5,width=10)
##D # Create edgelist:
##D dat.3 <- matrix(c(1:15*2-1,1:15*2),,2)
##D dat.3 <- cbind(dat.3,round(seq(-0.7,0.7,length=15),1))
##D # Create grid layout:
##D L.3 <- matrix(1:30,nrow=2)
##D # Different esize:
##D qgraph(dat.3,layout=L.3,directed=FALSE,edge.labels=TRUE,esize=14)
##D # Different esize, strongest edges omitted (note how 0.4 edge is now 
##D # just as wide as 0.7 edge in previous graph):
##D qgraph(dat.3[-c(1:3,13:15),],layout=L.3,nNodes=30,directed=FALSE,
##D        edge.labels=TRUE,esize=14)
##D # Different esize, with maximum:
##D qgraph(dat.3,layout=L.3,directed=FALSE,edge.labels=TRUE,esize=14,maximum=1)
##D title("maximum=1",line=2.5)
##D qgraph(dat.3[-c(1:3,13:15),],layout=L.3,nNodes=30,directed=FALSE,edge.labels=TRUE,
##D        esize=14,maximum=1)
##D title("maximum=1",line=2.5)
##D # Different minimum
##D qgraph(dat.3,layout=L.3,directed=FALSE,edge.labels=TRUE,esize=14,minimum=0.1)
##D title("minimum=0.1",line=2.5)
##D # With cutoff score:
##D qgraph(dat.3,layout=L.3,directed=FALSE,edge.labels=TRUE,esize=14,cut=0.4)
##D title("cut=0.4",line=2.5)
##D # With details:
##D qgraph(dat.3,layout=L.3,directed=FALSE,edge.labels=TRUE,esize=14,minimum=0.1,maximum=1,
##D        cut=0.4,details=TRUE)
##D title("details=TRUE",line=2.5)
##D # Trivial example of manually specifying edge color and widths:
##D E <- as.matrix(data.frame(from=rep(1:3,each=3),to=rep(1:3,3),width=1:9))
##D qgraph(E,mode="direct",edge.color=rainbow(9))
##D ### pcalg support ###
##D # Example from pcalg vignette:
##D library("pcalg")
##D data(gmI)
##D suffStat <- list(C = cor(gmI$x), n = nrow(gmI$x))
##D pc.fit <- pc(suffStat, indepTest=gaussCItest,
##D              p = ncol(gmI$x), alpha = 0.01)
##D qgraph(pc.fit)
## End(Not run)

[Package qgraph version 1.2 Index]