## ----setup, include = FALSE---------------------------------------------------
knitr::opts_chunk$set(collapse = TRUE, comment = "#>", fig.width = 7, fig.height = 6)
library(psychnets)
has_cograph <- requireNamespace("cograph", quietly = TRUE)
binary_data <- dichotomize(data = SRL_GPT, method = "rank")

## ----data-preview-------------------------------------------------------------
head(binary_data)

## ----fit-network--------------------------------------------------------------
ising_net <- psychnet(data = binary_data, method = "ising", rule = "AND")
ising_net

## ----summarize-network--------------------------------------------------------
summary(ising_net)

## ----fit-certificate----------------------------------------------------------
certificate(ising_net)

## ----node-centrality----------------------------------------------------------
net_centralities(ising_net)

## ----node-predictability------------------------------------------------------
net_predict(ising_net, data = binary_data)

## ----fit-unregularized--------------------------------------------------------
unregularized_net <- psychnet(data = binary_data, method = "ising_sampler", alpha = 0.05)
unregularized_net

## ----summarize-unregularized--------------------------------------------------
summary(unregularized_net)

## ----certify-unregularized----------------------------------------------------
certificate(unregularized_net)

## ----plot-network, eval = has_cograph-----------------------------------------
cograph::splot(ising_net, psych_styling = TRUE, predictability = TRUE)