Carlisle Rainey carlislerainey

## all-policies.csv

          
            Category
            Issue
            Policy

            
              Economic
              Drug Costs
              allowing imported drugs from Canada

            
              Economic
              Drug Costs
              eliminate drug advertisements

            
              Economic
              Drug Costs
              requiring to pay higher share in drugs

            
              Economic
              Education
              free state college tuition

            
              Economic
              Energy
              adding monthly charge to utility bill to combat climate change

            
              Economic
              Energy
              carbon dioxide emission limits

            
              Economic
              Energy
              coal

            
              Economic
              Energy
              drilling

            
              Economic
              Energy
              energy efficiency

## pilot-se.R
library(tidyverse)
library(DeclareDesign)

# Original parameters
tau <- 1  # treatment effect
se <- tau / (qnorm(0.95) + qnorm(0.80))  # standard error for 80% power
n_planned <- 500  # sample size per condition in planned full study
# calculate required standard deviation to yield 80% power given the above
sigma <- se * sqrt(2 * n_planned / 2)

## br-separation-illustration.R
# load packages
library(modelsummary)

# get latest version of {crdata} package, if updated
remotes::install_github("carlislerainey/crdata")

# load (and slightly wrangle) data from Barrilleaux and Rainey (2014)
br <- crdata::br2014 %>%
  # recode from centered GOP gov. indicator to 0/1 Dem. gov. indicator
  # (explanatory variables are centered about mean)

## illustrate-display.R
# load packages
library(tidyverse)

# update {crdata} if necessary
remotes::install_github("carlislerainey/crdata")

# load data
weis <- crdata::weisiger2014

# rescale weisiger2014 explanatory variables using arm::rescale()

## starter-lm.R

# load packages
library(tidyverse)

# create data frame of the potential outcomes
po <- tribble(
  ~Name,        ~Y1, ~Y0,
  "Alex Smith",     7,   5,
  "Jamie Doe",      2,   3,
  "Pat Johnson",    7,   7,

## compute-coverage.R

# load packages
library(tidyverse)

# create data frame of the potential outcomes
po <- tribble(
  ~Name,        ~Y1, ~Y0,
  "Alex Smith",     7,   5,
  "Jamie Doe",      2,   3,
  "Pat Johnson",    7,   7,

## starter.R

# load packages
library(tidyverse)

# create data frame of the potential outcomes
po <- tribble(
  ~Name,        ~Y1, ~Y0,
  "Alex Smith",     7,   5,
  "Jamie Doe",      2,   3,
  "Pat Johnson",    7,   7,

## coin-toss-in-stan.R
# load packages
library(rstan)
library(bayesplot)

# make a stan model
fancy_stan_model <- "
generated quantities {
    int<lower=0, upper=1> y_sim = bernoulli_rng(0.5);
}
"

## comparing.R
# load packages
library(tidyverse)
library(marginaleffects)
library(rstanarm); options(mc.cores = parallel::detectCores())

# load data
data <- read_rds("https://www.dropbox.com/s/9grn8kkb5yzwagx/data.rds?raw=1") %>%
  filter(passed_mvc1) %>%
  glimpse()

## animated-sharing.R

# load packages
library(tidyverse)
library(ggrepel)
library(gganimate)

# set ggplot options
theme_set(theme_bw(base_family = "Gill Sans"))
update_geom_defaults("label", list(family = theme_get()$text$family))
update_geom_defaults("text", list(family = theme_get()$text$family))
Category	Issue	Policy
Economic	Drug Costs	allowing imported drugs from Canada
Economic	Drug Costs	eliminate drug advertisements
Economic	Drug Costs	requiring to pay higher share in drugs
Economic	Education	free state college tuition
Economic	Energy	adding monthly charge to utility bill to combat climate change
Economic	Energy	carbon dioxide emission limits
Economic	Energy	coal
Economic	Energy	drilling
Economic	Energy	energy efficiency
	library(tidyverse)
	library(DeclareDesign)

	# Original parameters
	tau <- 1 # treatment effect
	se <- tau / (qnorm(0.95) + qnorm(0.80)) # standard error for 80% power
	n_planned <- 500 # sample size per condition in planned full study
	# calculate required standard deviation to yield 80% power given the above
	sigma <- se * sqrt(2 * n_planned / 2)
	# load packages
	library(modelsummary)

	# get latest version of {crdata} package, if updated
	remotes::install_github("carlislerainey/crdata")

	# load (and slightly wrangle) data from Barrilleaux and Rainey (2014)
	br <- crdata::br2014 %>%
	# recode from centered GOP gov. indicator to 0/1 Dem. gov. indicator
	# (explanatory variables are centered about mean)
	# load packages
	library(tidyverse)

	# update {crdata} if necessary
	remotes::install_github("carlislerainey/crdata")

	# load data
	weis <- crdata::weisiger2014

	# rescale weisiger2014 explanatory variables using arm::rescale()

	# load packages
	library(tidyverse)

	# create data frame of the potential outcomes
	po <- tribble(
	~Name, ~Y1, ~Y0,
	"Alex Smith", 7, 5,
	"Jamie Doe", 2, 3,
	"Pat Johnson", 7, 7,
	# load packages
	library(rstan)
	library(bayesplot)

	# make a stan model
	fancy_stan_model <- "
	generated quantities {
	int<lower=0, upper=1> y_sim = bernoulli_rng(0.5);
	}
	"
	# load packages
	library(tidyverse)
	library(marginaleffects)
	library(rstanarm); options(mc.cores = parallel::detectCores())

	# load data
	data <- read_rds("https://www.dropbox.com/s/9grn8kkb5yzwagx/data.rds?raw=1") %>%
	filter(passed_mvc1) %>%
	glimpse()

	# load packages
	library(tidyverse)
	library(ggrepel)
	library(gganimate)

	# set ggplot options
	theme_set(theme_bw(base_family = "Gill Sans"))
	update_geom_defaults("label", list(family = theme_get()$text$family))
	update_geom_defaults("text", list(family = theme_get()$text$family))