Deleetdk

### ANALYTIC REPLICATIONS OF NOAH CARL'S Explaining Terrorism Threat Level Across Western Countries


# libs --------------------------------------------------------------------

library(pacman)
p_load(XLConnect, kirkegaard, psych, weights, magrittr, effsize, lsr, compute.es, MASS)


# data --------------------------------------------------------------------

Deleetdk

### EGYPTIAN SKULLS ANALYSIS

# libs --------------------------------------------------------------------
library(pacman)
p_load(ggplot2, ade4, magrittr, reshape2, kirkegaard, plyr, psych)


# data --------------------------------------------------------------------
#load
data(skulls)

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library(pacman)
p_load(ggplot2, dkstat, stringr, plyr, kirkegaard)

#install kirkegaard and dkstat from github if needed
#library("devtools")
#install_github("deleetdk/kirkegaard")
#install_github("rOpenGov/dkstat")

# load data ---------------------------------------------------------------
#get meta-data

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library(pacman)
p_load(haven, dplyr, kirkegaard)


# load data ---------------------------------------------------------------
entiredata = read.csv("Woodcock-Johnson Murray_2007.csv")

# subset ------------------------------------------------------------------
#only first two races, and two other conditions
d = subset(entiredata, racesample < 3 & wj == 1 & sample == 1)

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library(pacman)
p_load(kirkegaard, magrittr, ggplot2)

# example dataset ---------------------------------------------------------

set.seed(1)
iris_miss = df_addNA(iris)

# amount ------------------------------------------------------------------

Deleetdk

### THIS IS NOW MOSTLY REDUNDANT
### SHINY VERSION HERE: https://github.com/Deleetdk/brexit_model

# libs --------------------------------------------------------------------
library(pacman)
p_load(lubridate, rvest, stringr, kirkegaard, ggplot2, scales, boot)


# scrape data -------------------------------------------------------------
#get newest data on website

Deleetdk

### re-analyze Beaver and Wright's correlation matrix
library(magrittr)

# load data ---------------------------------------------------------------
#load matrix
d_bw = structure(list(IQ = c(1, -0.4, -0.44, -0.29, -0.51, -0.58, -0.54, -0.52, -0.53, -0.49, -0.43, -0.56, -0.27, -0.46, -0.38), Property.crime = c(-0.4, 1, 0.95, 0.97, 0.76, 0.77, 0.69, 0.72, 0.93, 0.32, 0.44, 0.56, 0.12, 0.13, 0.16), Burglary = c(-0.44, 0.95, 1, 0.88, 0.7, 0.79, 0.68, 0.75, 0.92, 0.46, 0.56, 0.64, 0.25, 0.27, 0.27), Larceny = c(-0.29, 0.97, 0.88, 1, 0.59, 0.64, 0.53, 0.62, 0.83, 0.27, 0.42, 0.5, 0.13, 0.05, 0.09), Motor.vehicle.theft = c(-0.51, 0.76, 0.7, 0.59, 1, 0.84, 0.88, 0.69, 0.89, 0.19, 0.18, 0.44, -0.09, 0.13, 0.14), Violent.crime = c(-0.58, 0.77, 0.79, 0.64, 0.84, 1, 0.91, 0.93, 0.94, 0.57, 0.6, 0.76, 0.23, 0.46, 0.39), Robbery = c(-0.54, 0.69, 0.68, 0.53, 0.88, 0.91, 1, 0.7, 0.87, 0.36, 0.38, 0.62, 0.03, 0.28, 0.23), Aggravated.assault = c(-0.52, 0.72, 0.75, 0.62, 0.69, 0.93, 0.7, 1, 0.86, 0.66, 0.69, 0.76, 0.36, 0.55, 0

Deleetdk

library(pacman)
p_load(curl, kirkegaard)


# fetch lists of stations -------------------------------------------------

for (i in 1:56) {
  message(i)
  
  #if i < 10, pad 0

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#!/bin/bash
for ID in {1..56}
	do
		#pad 0's
		size = ${#ID}

		if [ $size == 1 ]
			then
			ID = "0" + $ID
		fi

Deleetdk

# libs --------------------------------------------------------------------
library(pacman)
p_load(stringr, psych, kirkegaard, psychometric)


# data --------------------------------------------------------------------
d_table = read.csv("chorion_data.csv", row.names = 1)

# extract data ------------------------------------------------------------
#find MC and DC rows