View source: R/f_convenience_getmatrix.R
getmatrix | R Documentation |
This function will extract an estimated matrix, and will either return a single matrix for single group models or a list of such matrices for multiple group models.
getmatrix(x, matrix, group, threshold = FALSE, alpha = 0.01,
adjust = c("none", "holm", "hochberg", "hommel",
"bonferroni", "BH", "BY", "fdr"), mode = c("tested",
"all"), diag = TRUE)
x |
A |
matrix |
String indicating the matrix to be extracted. |
group |
Integer indicating the group for the matrix to be extracted. |
threshold |
Logical. Should the matrix be thresholded (non-significant values set to zero? Can also be a value with an absolute threshold below wich parameters are set to zero.) |
alpha |
Significance level to use. |
adjust |
p-value adjustment method to use. See |
mode |
Mode for adjusting for multiple comparisons. Should all parameters be considered as the total number of tests or only the tested parameters (parameters of interest)? |
diag |
Set to FALSE to set diagonal elements to zero. |
A matrix of parameter estimates, of a list of such matrices for multiple group models.
Sacha Epskamp
# 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 a full GGM:
mod <- ggm(ConsData, vars = vars, omega = "full")
# Run model:
mod <- mod %>% runmodel
# Obtain network:
mod %>% getmatrix("omega")
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