## ----setup, include = FALSE---------------------------------------------------
knitr::opts_chunk$set(collapse = TRUE, comment = "#>", fig.width = 7, fig.height = 6)
library(psychnets)
has_cograph <- requireNamespace("cograph", quietly = TRUE)
mixed_data <- data.frame(
  CSU = SRL_GPT$CSU,
  IV = SRL_GPT$IV,
  SE = SRL_GPT$SE,
  SR_hi = as.integer(SRL_GPT$SR >= median(SRL_GPT$SR)),
  TA_hi = as.integer(SRL_GPT$TA >= median(SRL_GPT$TA))
)

## ----data-preview-------------------------------------------------------------
head(mixed_data)

## ----fit-network--------------------------------------------------------------
mixed_net <- psychnet(data = mixed_data, method = "mgm")
mixed_net

## ----summarize-network--------------------------------------------------------
summary(mixed_net)

## ----fit-certificate----------------------------------------------------------
certificate(mixed_net)

## ----node-centrality----------------------------------------------------------
net_centralities(mixed_net)

## ----node-predictability------------------------------------------------------
net_predict(mixed_net, data = mixed_data)

## ----fit-or-rule--------------------------------------------------------------
mixed_or <- psychnet(data = mixed_data, method = "mgm", rule = "OR")
mixed_or

## ----summarize-or-rule--------------------------------------------------------
summary(mixed_or)

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