CIplot: Plot Analytic Confidence Intervals

In psychonetrics: Structural Equation Modeling and Confirmatory Network Analysis

Description

Function to plot analytic confidence intervals (CI) of matrix elements estimated in psychonetrics.

Usage

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)

Arguments

x	A psychonetrics model.
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 labels for square matrices.
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

Value

A single ggplot2 object, or a list of ggplot2 objects for each matrix requested.

Author(s)

Sacha Epskamp

Examples

### 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")

psychonetrics documentation built on Oct. 26, 2021, 1:06 a.m.