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"LD_* scout runtime" information: | |
{ | |
"can-write-uinput" : true, | |
"steam-installation" : { | |
"path" : "/home/emil/.steam", | |
"data_path" : "/home/emil/.steam", | |
"bin32_path" : "/home/emil/.steam/ubuntu12_32", | |
"steamscript_path" : "/usr/bin/steam", | |
"steamscript_version" : "1.0.0.78", | |
"issues" : [ |
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System: | |
Host: computer Kernel: 5.15.0-89-generic x86_64 bits: 64 | |
Desktop: Cinnamon 5.6.8 Distro: Linux Mint 21.1 Vera | |
Machine: | |
Type: Desktop System: ASUS product: N/A v: N/A serial: <superuser required> | |
Mobo: ASUSTeK model: Pro WS WRX80E-SAGE SE WIFI II v: Rev 1.xx | |
serial: <superuser required> UEFI: American Megatrends v: 0204 | |
date: 11/10/2022 | |
CPU: | |
Info: 16-core model: AMD Ryzen Threadripper PRO 5955WX s bits: 64 |
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library(googlesheets4) | |
library(kirkegaard) | |
theme_set(theme_bw()) | |
#read data | |
d = read_sheet("https://docs.google.com/spreadsheets/d/1cPApEVEPNj4DXTB7LN7hd7B6WxYQiottbfHFt72tCzE/edit#gid=0") | |
#transform to long form for plotting | |
d_long = d %>% |
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library(tidyverse) | |
#simulate datasets | |
sibs = 20 | |
x = map_df(seq(0, 1, .01), function(r) { | |
#simulate sibling scores at correlation r | |
matrix = matrix(r, ncol = sibs, nrow = sibs) | |
diag(matrix) = 1 | |
mvrnorm(n = 1e4, | |
Sigma = matrix, |
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library(kirkegaard) | |
#get cors with p values | |
cors = iris[-5] %>% | |
wtd.cor() | |
cors = mpg[map_lgl(mpg, is.numeric)] %>% | |
wtd.cor() | |
#long format |
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#!/usr/bin/env Rscript | |
library(stringr) | |
#scape spaces | |
escape_spaces = function(x) { | |
str_replace_all(x, fixed(" "), "\\ ") | |
} | |
#get args | |
args = commandArgs(trailingOnly=TRUE) |
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#CRAN versions dont work | |
#devtools::install_github("lmullen/gender") | |
#devtools::install_github("lmullen/genderdata") | |
library(rvest) | |
library(kirkegaard) | |
library(gender) | |
library(patchwork) | |
theme_set(theme_classic()) |
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/* | |
Function | |
This bookmarklet helps you quickly search Google Scholar for a given string with added keywords. | |
By default these keywords are words related to mortality of diseases: prognosis, life expectancy, natural history and mortality. | |
You can change them below. | |
How to use | |
Make a new bookmark. In the location, place the javascript code below. | |
*/ | |
javascript:(function(){ |
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### 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 |
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### REPLICATION OF DUNKEL AND DUTTON 2016 | |
# Religiosity as a predictor of in-group favoritism within and between religious groups | |
# This assumes you have the OKCupid data loaded as d_main with various variables already created. | |
# recode ------------------------------------------------------------------ | |
#own race preference | |
d_main$prefer_own_race = (d_main$q123 == "Yes") %>% as.factor() | |
table(d_main$prefer_own_race) | |
#religious |
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