carlislerainey

##########################################
## A Function to Combine Estimates from MI
##########################################

comb.mi <- function(models) {
  
  # Arguments
  #   models:  a list of models, one estimated on each of m MI data sets.
  
  # Note: I borrow the notation below mostly from Rubin's *Multiple Imputation 

carlislerainey

# log-likelihood for beta
ll.fn.beta <- function(theta, y) {
  alpha <- theta[1]  # optim() requires a single parameter vector
  beta <- theta[2]
  ll <- alpha*sum(log(y)) + beta*sum(log(1 - y)) - 
    length(y)*log(beta(alpha, beta))
  return(ll)
}

# function to estimate beta model

carlislerainey

# define log-likelihood function
ll.logit <- function(beta, y, X) {
  p <- plogis(X%*%beta)
  loglik <- sum(y*log(p)) + sum((1 - y)*log(1 - p))
  return(loglik)
}

# optimize
logit <- function(y, X) {
  init.par <- rep(0, ncol(X))

carlislerainey

# load packages
library(foreign)  # for read.dta()
library(arm)  # for display()

# load data
fl <- read.dta("http://crain.co/am-files/data/fearon-laitin.dta")

# something weird is going on
table(fl$onset)  # wtf?
fl$onset[fl$onset == 4] <- 1 # recode weird case

carlislerainey

# load libraries
library(arm)

# read data
d <- read.csv("http://crain.co/am-files/data/turnout-small.csv")

# estimate simple logit model
m <- glm(vote ~ educate + age + income, 
         family = binomial, data = d)

carlislerainey

# load packages
library(MASS)
library(compactr)
library(compactr)

# read data
d <- read.csv("http://crain.co/am-files/data/hks.tab", sep = "\t")
keep <- c("osvAll", "troopLag", "policeLag", "militaryobserversLag",
          "brv_AllLag", "osvAllLagDum", "incomp", "epduration", "lntpop",

carlislerainey

# replication of Hill, Moore, and Mukherjee (2013)

# load packages
library(arm)

# load data
d <- read.csv("http://crain.co/am-files/data/hmm.csv")

# examine data

carlislerainey

d <- read.dta("http://crain.co/am-files/data/nes92.dta")

f <- vote ~ conservative + education + union + 
  income + black + distance_to_clinton + 
  distance_to_bush + economy_worse

carlislerainey

# install packages (if necessary)
install.packages("devtools")
install.packages("arm")

# install separation and compactr from GitHub
devtools::install_github("carlislerainey/compactr")
devtools::install_github("carlislerainey/separation")

# load packages
library(separation)

carlislerainey

n <- 0
k <- 0

a <- c(1, 2, 3, 4, 5)
b <- c(1, 2, 3, 4, 5)
col <- 1:length(a)
names <- c("Carlisle", "B", "C", "D", "E")

plot(NULL, xlim = c(0, 1), ylim = c(0, 3),
     xlab = expression(pi),