qgraph examples

qgraph

qgraph

qgraph

BIG 5 DATASET

# Load big5 dataset:
data(big5)
data(big5groups)

# 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-2


# Same graph with spring layout:
Q <- qgraph(Q, layout = "spring")
title("Big 5 correlations", line = 2.5)

plot of chunk unnamed-chunk-2


# Same graph with Venn diagram overlay:
qgraph(Q, overlay = TRUE)
title("Big 5 correlations", line = 2.5)

plot of chunk unnamed-chunk-2


# Same graph with different color scheme:
qgraph(Q, posCol = "blue", negCol = "purple")
title("Big 5 correlations", line = 2.5)

plot of chunk unnamed-chunk-2


# Significance graph (circular):
qgraph(Q, graph = "sig", layout = "circular")
title("Big 5 correlations (p-values)", line = 2.5)

plot of chunk unnamed-chunk-2


# Significance graph:
qgraph(Q, graph = "sig")
title("Big 5 correlations (p-values)", line = 2.5)

plot of chunk unnamed-chunk-2


# Significance graph (distinguishing positive and negative statistics):
qgraph(Q, graph = "sig2")
title("Big 5 correlations (p-values)", line = 2.5)

plot of chunk unnamed-chunk-2


# Grayscale graphs:
qgraph(Q, gray = TRUE, layout = "circular")
title("Big 5 correlations", line = 2.5)

plot of chunk unnamed-chunk-2


qgraph(Q, graph = "sig", gray = TRUE)
title("Big 5 correlations (p-values)", line = 2.5)

plot of chunk unnamed-chunk-2


# Correlations graph with scores of random subject:
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))
title("Test scores of random subject", line = 2.5)

plot of chunk unnamed-chunk-2

layout(1)

# EFA:
big5efa <- factanal(big5, factors = 5, rotation = "promax", scores = "regression")
qgraph(big5efa, groups = big5groups, layout = "circle", rotation = "promax", 
    minimum = 0.2, cut = 0.4, vsize = c(1.5, 15), borders = FALSE, vTrans = 200)
title("Big 5 EFA", line = 2.5)

plot of chunk unnamed-chunk-2


# PCA:
library("psych")
big5pca <- principal(cor(big5), 5, rotate = "promax")
qgraph(big5pca, groups = big5groups, layout = "circle", rotation = "promax", 
    minimum = 0.2, cut = 0.4, vsize = c(1.5, 15), borders = FALSE, vTrans = 200)
title("Big 5 PCA", line = 2.5)

plot of chunk unnamed-chunk-2

UNWEIGHTED DIRECTED GRAPHS

set.seed(1)
adj = matrix(sample(0:1, 10^2, TRUE, prob = c(0.8, 0.2)), nrow = 10, ncol = 10)
qgraph(adj)
title("Unweighted and directed graphs", line = 2.5)

plot of chunk unnamed-chunk-3


# Save plot to nonsquare pdf file:
qgraph(adj, filetype = "pdf", height = 5, width = 10)

EXAMPLES FOR EDGES UNDER DIFFERENT ARGUMENTS

# Create edgelist:
dat.3 <- matrix(c(1:15 * 2 - 1, 1:15 * 2), , 2)
dat.3 <- cbind(dat.3, round(seq(-0.7, 0.7, length = 15), 1))

# Create grid layout:
L.3 <- matrix(1:30, nrow = 2)

# Different esize:
qgraph(dat.3, layout = L.3, directed = FALSE, edge.labels = TRUE, esize = 14)

plot of chunk unnamed-chunk-4


# Different esize, strongest edges omitted (note how 0.4 edge is now just
# as wide as 0.7 edge in previous graph):
qgraph(dat.3[-c(1:3, 13:15), ], layout = L.3, nNodes = 30, directed = FALSE, 
    edge.labels = TRUE, esize = 14)

plot of chunk unnamed-chunk-4


# Different esize, with maximum:
qgraph(dat.3, layout = L.3, directed = FALSE, edge.labels = TRUE, esize = 14, 
    maximum = 1)
title("maximum=1", line = 2.5)

plot of chunk unnamed-chunk-4


qgraph(dat.3[-c(1:3, 13:15), ], layout = L.3, nNodes = 30, directed = FALSE, 
    edge.labels = TRUE, esize = 14, maximum = 1)
title("maximum=1", line = 2.5)

plot of chunk unnamed-chunk-4


# Different minimum
qgraph(dat.3, layout = L.3, directed = FALSE, edge.labels = TRUE, esize = 14, 
    minimum = 0.1)
title("minimum=0.1", line = 2.5)

plot of chunk unnamed-chunk-4


# With cutoff score:
qgraph(dat.3, layout = L.3, directed = FALSE, edge.labels = TRUE, esize = 14, 
    cut = 0.4)
title("cut=0.4", line = 2.5)

plot of chunk unnamed-chunk-4


# With details:
qgraph(dat.3, layout = L.3, directed = FALSE, edge.labels = TRUE, esize = 14, 
    minimum = 0.1, maximum = 1, cut = 0.4, details = TRUE)
title("details=TRUE", line = 2.5)

plot of chunk unnamed-chunk-4

Additional topics


# Trivial example of manually specifying edge color and widths:
E <- as.matrix(data.frame(from = rep(1:3, each = 3), to = rep(1:3, 3), width = 1:9))
qgraph(E, mode = "direct", edge.color = rainbow(9))

plot of chunk unnamed-chunk-5

pcalg support

# Example from pcalg vignette:
library("pcalg")
data(gmI)
suffStat <- list(C = cor(gmI$x), n = nrow(gmI$x))
pc.fit <- pc(suffStat, indepTest = gaussCItest, p = ncol(gmI$x), alpha = 0.01)

qgraph(pc.fit)

qgraph.cfa

# Simulate dataset:
set.seed(2)
eta <- matrix(rnorm(200 * 5), ncol = 5)
lam <- matrix(rnorm(50 * 5, 0, 0.15), 50, 5)
lam[apply(diag(5) == 1, 1, rep, each = 10)] <- rnorm(50, 0.7, 0.3)
th <- matrix(rnorm(200 * 50), ncol = 50)
Y <- eta %*% t(lam) + th

# Create groupslist
gr <- list(1:10, 11:20, 21:30, 31:40, 41:50)

# Using 'lavaan' package:
res <- qgraph.cfa(cov(Y), N = 200, groups = gr, pkg = "lavaan", vsize.man = 2, 
    vsize.lat = 10)

plot of chunk unnamed-chunk-7


qgraph.lavaan(res, filename = "lavaan", legend = FALSE, groups = gr, edge.label.cex = 0.6)

## [1] "Output stored in /home/sacha/Documents/phd/R/lavaan.pdf"


# Using 'sem' package:
res <- qgraph.cfa(cov(Y), N = 200, groups = gr, pkg = "sem", vsize.man = 2, 
    vsize.lat = 10, fun = qgraph.loadings)

plot of chunk unnamed-chunk-7


qgraph.semModel(res, edge.label.cex = 0.6)

plot of chunk unnamed-chunk-7


qgraph(res, edge.label.cex = 0.6)

plot of chunk unnamed-chunk-7


qgraph.sem(res, filename = "sem", legend = FALSE, groups = gr, edge.label.cex = 0.6)

## [1] "Output stored in /home/sacha/Documents/phd/R/sem.pdf"

Big 5 dataset

data(big5)
data(big5groups)

fit <- qgraph.cfa(cov(big5), nrow(big5), big5groups, pkg = "lavaan", opts = list(se = "none"), 
    vsize.man = 1, vsize.lat = 6, edge.label.cex = 0.5)

plot of chunk unnamed-chunk-8

print(fit)

## lavaan (0.5-11) converged normally after 128 iterations
## 
##   Number of observations                           500
## 
##   Estimator                                         ML
##   Minimum Function Test Statistic            60838.192
##   Degrees of freedom                             28430
##   P-value (Chi-square)                           0.000

qgraph.layout.fruchtermanreingold

# This example makes a multipage PDF that contains images Of a building
# network using soft constraints.

# Each step one node is added with one edge. The max.delta decreases the
# longer nodes are present in the network.

pdf("Soft Constraints.pdf", width = 10, height = 5)

adj = adjO = matrix(0, nrow = 3, ncol = 3)
adj[upper.tri(adj)] = 1
Q = qgraph(adj, vsize = 3, height = 5, width = 10, layout = "spring", esize = 1, 
    filetype = "", directed = T)
cons = Q$layout
for (i in 1:20) {
    x = nrow(adj)
    adjN = matrix(0, nrow = x + 1, ncol = x + 1)
    adjN[1:x, 1:x] = adj
    consN = matrix(NA, nrow = x + 1, ncol = 2)
    consN[1:x, ] = cons[1:x, ]
    layout.par = list(init = rbind(cons, c(0, 0)), max.delta = 10/(x + 1):1, 
        area = 10^2, repulse.rad = 10^3)
    y = sample(c(x, sample(1:(x), 1)), 1)
    adjN[y, x + 1] = 1
    Q = qgraph(adjN, Q, layout = "spring", layout.par = layout.par)
    cons = Q$layout
    adj = adjN
}
dev.off()

## pdf 
##   2

qgraph_loadings

# Load big5 dataset:
data(big5)
data(big5groups)

big5efa <- factanal(big5, factors = 5, rotation = "promax", scores = "regression")
big5loadings <- loadings(big5efa)
qgraph.loadings(big5loadings, groups = big5groups, rotation = "promax", minimum = 0.2, 
    cut = 0.4, vsize = c(1.5, 15), borders = FALSE, vTrans = 200)

plot of chunk unnamed-chunk-10


# Tree layout:
qgraph.loadings(big5loadings, groups = big5groups, rotation = "promax", minimum = 0.2, 
    cut = 0.4, vsize = c(1.5, 15), borders = FALSE, vTrans = 200, layout = "tree", 
    width = 20, filetype = "R")

qgraph_svg

VISUALIZE CORRELATION MATRIX

eta = matrix(rnorm(200 * 5), ncol = 5)
lam = matrix(0, nrow = 100, ncol = 5)
for (i in 1:5) lam[(20 * i - 19):(20 * i), i] = rnorm(20, 0.7, 0.3)
eps = matrix(rnorm(200 * 100), ncol = 100)
Y = eta %*% t(lam) + eps

tooltips = paste("item", 1:100)
groups = list(1:20, 21:40, 41:60, 61:80, 81:100)
names(groups) = paste("Factor", LETTERS[1:5])
# Run qgraph:

qgraph_pca

data(big5)
data(big5groups)

qgraph.pca(cor(big5), 5, groups = big5groups, rotation = "promax", minimum = 0.2, 
    cut = 0.4, vsize = c(1, 7), borders = FALSE, vTrans = 200)

plot of chunk unnamed-chunk-12


# Tree layout:
qgraph.pca(cor(big5), 5, groups = big5groups, rotation = "promax", minimum = 0.2, 
    cut = 0.4, vsize = c(1.5, 15), borders = FALSE, layout = "tree", width = 20, 
    filetype = "R")

qgraph_efa

data(big5)
data(big5groups)

qgraph.efa(big5, 5, groups = big5groups, rotation = "promax", minimum = 0.2, 
    cut = 0.4, vsize = c(1, 7), borders = FALSE, vTrans = 200)

plot of chunk unnamed-chunk-13


# Tree layout:
qgraph.efa(big5, 5, groups = big5groups, rotation = "promax", minimum = 0.2, 
    cut = 0.4, vsize = c(1, 7), borders = FALSE, layout = "tree", width = 20, 
    filetype = "R")

qgraph.panel

data(big5)
data(big5groups)

qgraph.panel(cor(big5), groups = big5groups, minimum = 0.2, borders = FALSE, 
    vsize = 1, cut = 0.3)

plot of chunk unnamed-chunk-14

centrality

set.seed(1)
adj <- matrix(sample(0:1, 10^2, TRUE, prob = c(0.8, 0.2)), nrow = 10, ncol = 10)
Q <- qgraph(adj)

plot of chunk unnamed-chunk-15


centrality(Q)

## $OutDegree
##  [1] 3 2 0 2 1 2 2 1 2 2
## 
## $InDegree
##  [1] 3 1 2 1 1 1 2 4 0 2
## 
## $Closeness
##  [1] 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.04 0.00
## 
## $Betweenness
##  [1] 28 13  0 12 12 12 10 13  0 14
## 
## $ShortestPathLengths
##       [,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10]
##  [1,]    0    3    1    2    1    4    1    2  Inf     3
##  [2,]    2    0    3    4    3    1    3    1  Inf     5
##  [3,]  Inf  Inf    0  Inf  Inf  Inf  Inf  Inf  Inf   Inf
##  [4,]    1    3    2    0    2    4    2    2  Inf     1
##  [5,]    2    4    3    1    0    5    3    3  Inf     2
##  [6,]    1    2    2    3    2    0    2    1  Inf     4
##  [7,]    1    2    2    3    2    3    0    1  Inf     4
##  [8,]    3    1    4    5    4    2    4    0  Inf     6
##  [9,]    3    3    1    5    4    4    2    2    0     1
## [10,]    2    2    3    4    3    3    1    1  Inf     0
## 
## $ShortestPaths
##       [,1]   [,2]   [,3]   [,4]   [,5]   [,6]   [,7]   [,8]   [,9]  
##  [1,] List,0 List,1 List,1 List,1 List,1 List,1 List,1 List,1 List,0
##  [2,] List,1 List,0 List,1 List,1 List,1 List,1 List,1 List,1 List,0
##  [3,] List,0 List,0 List,0 List,0 List,0 List,0 List,0 List,0 List,0
##  [4,] List,1 List,1 List,1 List,0 List,1 List,1 List,2 List,1 List,0
##  [5,] List,1 List,1 List,1 List,1 List,0 List,1 List,2 List,1 List,0
##  [6,] List,1 List,1 List,1 List,1 List,1 List,0 List,1 List,1 List,0
##  [7,] List,1 List,1 List,1 List,1 List,1 List,1 List,0 List,1 List,0
##  [8,] List,1 List,1 List,1 List,1 List,1 List,1 List,1 List,0 List,0
##  [9,] List,1 List,1 List,1 List,1 List,1 List,1 List,1 List,1 List,0
## [10,] List,1 List,1 List,1 List,1 List,1 List,1 List,1 List,1 List,0
##       [,10] 
##  [1,] List,1
##  [2,] List,1
##  [3,] List,0
##  [4,] List,1
##  [5,] List,1
##  [6,] List,1
##  [7,] List,1
##  [8,] List,1
##  [9,] List,1
## [10,] List,0

Comments are closed.