View source: R/f_convenience_CIplot.R
CIplot | R Documentation |
Function to plot analytic confidence intervals (CI) of matrix elements estimated in psychonetrics.
CIplot(x, matrices, alpha_ci = 0.05, alpha_color = c(0.05,
0.01, 0.001, 1e-04), labels, labels2, labelstart,
print = TRUE, major_break = 0.2, minor_break = 0.1,
split0, prop0, prop0_cex = 1, prop0_alpha = 0.95,
prop0_minAlpha = 0.25)
x |
A |
matrices |
Vector of strings indicating the matrices to plot CIs for |
alpha_ci |
The alpha level used for the CIs |
alpha_color |
A vector of alphas used for coloring the CIs |
labels |
The labels for the variables associated with the rows of a matrix. |
labels2 |
The labels for the variables associated with the columns of a matrix. Defaults to the value of |
labelstart |
The value to determine if labels are printed to the right or to the left of the CI |
print |
Logical, should the plots also be printed? Only works when one matrix is used in 'matrices' |
major_break |
Numeric indicating the step size between major breaks |
minor_break |
Numeric indicating the step size between minor breaks |
split0 |
Logical only used for results of |
prop0 |
Logical only used for results of |
prop0_cex |
Only used for results of |
prop0_alpha |
Only used for results of |
prop0_minAlpha |
Only used for results of |
A single ggplot2 object, or a list of ggplot2 objects for each matrix requested.
Sacha Epskamp
### Example from ?ggm ###
# Load bfi data from psych package:
library("psychTools")
data(bfi)
# Also load dplyr for the pipe operator:
library("dplyr")
# Let's take the agreeableness items, and gender:
ConsData <- bfi %>%
select(A1:A5, gender) %>%
na.omit # Let's remove missingness (otherwise use Estimator = "FIML)
# Define variables:
vars <- names(ConsData)[1:5]
# Let's fit an empty GGM:
mod0 <- ggm(ConsData, vars = vars)
# Run the model:
mod0 <- mod0 %>% runmodel
# Labels:
labels <- c(
"indifferent to the feelings of others",
"inquire about others' well-being",
"comfort others",
"love children",
"make people feel at ease")
# Plot the CIs:
CIplot(mod0, "omega", labels = labels, labelstart = 0.2)
### Example from ?gvar ###
library("dplyr")
library("graphicalVAR")
beta <- matrix(c(
0,0.5,
0.5,0
),2,2,byrow=TRUE)
kappa <- diag(2)
simData <- graphicalVARsim(50, beta, kappa)
# Form model:
model <- gvar(simData)
# Evaluate model:
model <- model %>% runmodel
# Plot the CIs:
CIplot(model, "beta")
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