SachaEpskamp

library("SEset")
library("qgraph")
library("pcalg")

# For true DAG:
A <- matrix(c(
  0,0.25,0.25,
  0,0,0,
  0,0,0
),3,3,byrow=TRUE)

SachaEpskamp

library("bootnet")
library("mvtnorm")
library("qgraph")

# Sample size:
n <- 40000

# Generate 10-node chain graph with positive edges:
net <- genGGM(10, propPositive = 1, constant = 1.1)

SachaEpskamp

\documentclass{article}

\usepackage[
    paperwidth=27cm,paperheight=13cm,
    margin=1cm,
    ]{geometry}
    
\usepackage{amsmath}
\usepackage{amsfonts}
\usepackage{amssymb}

SachaEpskamp

library("qgraph")

# https://twitter.com/EikoFried/status/1208502815099932685
# Symposia:
Symposia <- list(
  # 1. 
  centrality = c("Eiko Fried", "Ciaran O'Driscoll", "Joshua Buckman", "Donald Robinaugh", "Teague Henry", "Laura Bringmann"),
  
  computational = c("Julian Burger", "Donald Robinaugh", "Lucy Robinson", "Jonas Haslbeck", "Teague Henry", "Sacha Epskamp"),
  

SachaEpskamp

# FIML multilevel
# Model described in https://psyarxiv.com/8ha93/
# See also http://statmodel.com/bmuthen/articles/Article_055.pdf

# Load packages:
library("lavaan")
library("psychonetrics")
library("bootnet")
library("mvtnorm")
library("qgraph")

SachaEpskamp

library("psychonetrics")
library("psychTools")
library("dplyr")
data("bfi")

# Extraversion and Neuroticism items:
data <- bfi[,11:20]

# ggm model:
mod_ggm <- ggm(data, estimator = "FIML") %>% 

SachaEpskamp

library("lavaan")
library("psychonetrics")
library("dplyr")

# Generate data:
mod <- '
F1 =~ X1 + X2 + X3
F2 =~ X4 + X5 + X6
F3 =~ X7 + X8 + X9
G =~ F1 + F2 + F3

SachaEpskamp

library(shiny)
ui <- fluidPage(
  h4("Click on plot to start drawing, click again to pause. Draw from LEFT to RIGHT"),
  # sliderInput("mywidth", "width of the pencil", min=1, max=30, step=1, value=10),
  plotOutput("plot", width = "800px", height = "500px",
             hover=hoverOpts(id = "hover", delay = 100, delayType = "throttle", clip = TRUE, nullOutside = TRUE),
             click="click"),
  actionButton("reset", "RESET DRAWING"),
  textInput("userid","Write your participant ID"),
  downloadButton("downloadData", "Download data"))

SachaEpskamp

library("shiny")
library("psychonetrics")
library("IsingFit")
library("IsingSampler")
library("qgraph")

# Load networks:
trueNetwork <- read.csv('http://sachaepskamp.com/files/weiadj.csv')[,-1]
trueNetwork <- as.matrix(trueNetwork)
Symptoms <- rownames(trueNetwork) <- colnames(trueNetwork)

SachaEpskamp

# This script contains some functions to automate things:

cat("THIS FUNCTION IS OUTDATED, PLEASE SEE https://github.com/SachaEpskamp/RIVMgrowth")

# Function to automize dummy encoding:
rivm_lgc_dummy <- function(
  data, # Dataset
  design, # Design matrix, as in psychonetrics
  type = c("non-linear","linear"), # Type of analysis to do
  predictor_var, # Variable name of predictor (only one supported at the moment)