elliottmorris

###################################
# exploring the 538 package 
# code by G. Elliott Morris, @gelliottmorris
###################################

#install pacakges
install.packages(c("fivethirtyeight","ggplot2","dplyr","ggthemes"))

#load them
library(fivethirtyeight)

elliottmorris

##################################
# Code for house-correcting Trump approval polls
# Written by Alexander Agadjanian and G. Elliott Morris
# for use on Elliott's blog, TheCrosstab.com. 
# @a_agadjanian @GElliottMorris
#
# Github Gist lives at https://gist.github.com/elliottmorris/905bd514110ea7d0b599cfca8a8e7332
####################################
# libraries ####

elliottmorris

## R Code for Analysing the 2016 Cooperative Congressional Election Study
## Written by G. Elliott Morris
## @gelliottmorris | elliott@thecrosstab.com | TheCrosstab.com
## please do not replicate the analysis without permission.
##
## Additional info:
## DOWNLOAD DATA AT https://dataverse.harvard.edu/dataset.xhtml?persistentId=doi:10.7910/DVN/GDF6Z0
## Github Gist lives at: https://gist.github.com/elliottmorris/79141ff0f0c3824798ce3b84f18b817b

### libraries & functions ####

elliottmorris

## R Code for analysing AHCA CBO outlook and congress data
## Written by G. Elliott Morris
## @gelliottmorris | elliott@thecrosstab.com | TheCrosstab.com
## please do not replicate the analysis without permission.
##
## Additional info:
## DOWNLOAD DATA AT http://bit.ly/2oa0RPa
## Github Gist lives at: http://bit.ly/2nI5bZu

# libraries ####

elliottmorris

# Libraries, data, setup ####
rm(list=ls())
library(tidyverse)
library(gridExtra)
library(googlesheets)
source("~/Desktop/theme_elliott.R")


# load in data from Gsheet
my_sheets <- gs_ls()

elliottmorris

# function written by HuffPost Pollster's Natalie Jackson for the 2016 election
# ibraries and import --------

library(dplyr)
library('Matrix')

seat_data <- read.csv("seat_partisanship_demog.csv")  # read in a 435 
seat_data <- seat_data %>%
  select(clinton2016, obama2012, house2016, pct_nonwhite)

elliottmorris

library(tidyverse)
polls_2018 <- read_tsv("http://elections.huffingtonpost.com/pollster/api/v2/questions/18-US-House/poll-responses-clean.tsv") %>% 
    filter(month(end_date)>=6) %>% 
    mutate(Dem.Margin = Democrat-Republican) %>%
    group_by(mode) %>%
    mutate(mean_dem = mean(Dem.Margin))
    
ggplot(polls_2018,aes(x=Dem.Margin,fill=Dem.Margin>0,col=Dem.Margin>0)) + 
    geom_bar(width=0.8,alpha=0.5) + 
    scale_color_manual(values=c("TRUE"="blue","FALSE"="red")) + 

elliottmorris

vote_model <- brm(mvbind(vote_trump,vote_clinton) ~ 1 +
                    # pop level
                    state_clinton + state_black_pct + state_hispanic_pct + state_white_protestant + 
                    # group effects
                    (1|sex) + (1|race) + (1|age) + (1|edu) + (1|state_name) + (1|region) +
                    # interactions b/t group effects
                    (1|race:edu) + (1|age:edu) + (1|race:region),
                  data = cces,
                  family = bernoulli(link = "logit"),
                  # stan stuff

elliottmorris

# History files
.Rhistory
.Rapp.history

# Session Data files
.RData

# User-specific files
.Ruserdata

elliottmorris

# This file runs an analysis of 2020 Democratic primary polls to 
# assess relationships between candidate's polling averages using
# variance-covariance matrices.
# 
# Read more about it here: 
# https://thecrosstab.substack.com/p/buttigiegs-rise-has-cost-biden-and

rm(list=ls())
library(tidyverse)
library(lubridate)