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Data-Exercise-4.Rmd
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Data-Exercise-4.Rmd
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---
title: "Data Exercise 4"
author: "Devin Judge-Lord"
date: \today
output: pdf_document
header-includes: # Add any Latex packages you need (or use a preamble/template)
- \usepackage{setspace} # spacing text
---
```{r setup, include=FALSE}
# Sets defaults for R chunks
knitr::opts_chunk$set(echo = TRUE, # echo = TRUE means that your code will show
warning=FALSE,
message=FALSE,
# fig.path='Figs/', # where to save figures
fig.height = 3,
fig.width = 4,
fig.align = 'center')
# Add any R packages you require.
# Here are some we will use in 811:
requires <- c("tidyverse", # tidyverse includes dplyr and ggplot2
"broom",
"haven",
"devtools",
"magrittr",
"mvtnorm",
"here")
# Install any you don't have
to_install <- c(!requires %in% rownames(installed.packages()))
install.packages(c(requires[to_install], "NA"), repos = "https://cloud.r-project.org/" )
# Load all required R packages
library(tidyverse)
library(broom)
library(haven)
library(magrittr)
library(here)
library(ggplot2); theme_set(theme_bw()) # global plot theme
# Colorblind and greyscale print-friendly scales
options(
ggplot2.continuous.color = "viridis",
ggplot2.continuous.fill = "viridis"
)
scale_color_discrete <- function(...)
scale_color_viridis_d(..., begin = 0, end = .7)
scale_fill_discrete <- function(...)
scale_fill_viridis_d(..., begin = 0, end = .7)
```
<!-- Now an R chunk to set up Stata chunks -->
<!-- If you have Stata, make eval=TRUE -->
```{r Statasetup, include=FALSE, eval=FALSE}
if(!"Statamarkdown" %in% rownames(installed.packages())){
devtools::install_github("Hemken/Statamarkdown", dependencies = F)
}
library(Statamarkdown)
stataexe <- find_stata()
knitr::opts_chunk$set(engine.path = list(stata = stataexe))
```
<!-- Now a Stata chunk to make data -->
<!-- Replace 1234 with your seed and make eval = TRUE -->
```{stata, eval = FALSE}
net install PS813_EX4, from(https://faculty.polisci.wisc.edu/weimer)
PS813_EX4 1234
save "data/EX4.dta"
```
<!-- An R chunk to load data -->
```{r data}
d <- read_dta("data/EX4.dta") %>% zap_formats()
```
```{r model}
model <- glm(Probat ~ Take + Report + Night + Convict,
data=d,
family=binomial(link="logit"))
knitr::kable(tidy(model), digits = 3)
```
# Findings
\doublespacing
\Large
Lorem ipsum dolor sit amet, consectetur adipiscing elit, sed do eiusmod tempor incididunt ut labore et dolore magna aliqua. Ut enim ad minim veniam, quis nostrud exercitation ullamco laboris nisi ut aliquip ex ea commodo consequat. Duis aute irure dolor in reprehenderit in voluptate velit esse cillum dolore eu fugiat nulla pariatur. Excepteur sint occaecat cupidatat non proident, sunt in culpa qui officia deserunt mollit anim id est laborum.
# Discussion
Lorem ipsum dolor sit amet, consectetur adipiscing elit, sed do eiusmod tempor incididunt ut labore et dolore magna aliqua. Ut enim ad minim veniam, quis nostrud exercitation ullamco laboris nisi ut aliquip ex ea commodo consequat. Duis aute irure dolor in reprehenderit in voluptate velit esse cillum dolore eu fugiat nulla pariatur. Excepteur sint occaecat cupidatat non proident, sunt in culpa qui officia deserunt mollit anim id est laborum.
# Appendex