AaronGullickson

# Example of how to estimate ME inequality measure analytically and via 
# bootstrap based on:
# https://sociologicalscience.com/articles-v12-7-115/

# load libraries ----------------------------------------------------------

library(palmerpenguins)
library(marginaleffects)
library(tidyverse)

AaronGullickson

```{r}
#| label: tbl-reg
#| tbl-cap: Models predicting miles per gallon

# build your models here - change these
model1 <- lm(mpg~cyl+disp, data=mtcars)
model2 <- lm(mpg~cyl+disp+hp, data=mtcars)
model3 <- lm(mpg~cyl+disp+hp+wt, data=mtcars)

modelsummary(list(model1, model2, model3), output = "gt",

AaronGullickson

---
title: "Test"
html_document:
#    css: "style.css"
---

```{css custom-css, echo=FALSE}
caption {
  color: black;
  font-size: 1.2em;

AaronGullickson

Here are some links to resources for working with R Markdown shared for the Code Horizons course.

Using Markdown

• Markdown Live Preview - A useful tool for learning basic Markdown syntax.

• Markdown Cheat Sheet

Packages for Making Tables in R Markdown

AaronGullickson

# I showed you how you can use wesanderson colors in your ggplots if you want in class. This script breaks
# down how to do that. The first thing you need to do is intall the "wesanderson" library in your project.
# You can do this with the following R command:

install.packages("wesanderson")

# PLEASE NOTE: You only need to install this once per project, so don't put it in a script you are going to run. 

# Once it is installed, you can load it with a library call (and lets load ggplot2 at the same time)
library(wesanderson)

AaronGullickson

# put these library calls elsewhere
library(stringr)
library(dplyr)
library(ggplot2)

# A model for testing this out
model_PoliAff2 <- multinom(Poli_Aff~Race_Multi+birth_decade+I(Income/1000)+Education+Gender,
                          data=anes_combined)

# a function that will give you the average predicted proportions of party affilaition

AaronGullickson

####################################
# example_script.R
# A basic example script
# Aaron Gullickson
####################################

# Load Libraries ----------------------------------------------------------

library(ggplot2)
library(ggthemes)

AaronGullickson

#recoded_variable <- ifelse(true/false statement, replacement if true, original value)

#code missing values
#GSS$god <- ifelse(GSS$GOD==0 | GSS$GOD==8 | GSS$GOD==9, NA, GSS$GOD)
#summary(GSS$god)
#table(GSS$god, GSS$GOD, exclude=NULL)

#code numeric responses as categorical (factor)
GSS$god <- factor(GSS$GOD,
                   levels=1:6,

AaronGullickson

metro <- aggregate(cbind(pop_total,
                         pop_nh_white,
                         pop_nh_black)~met2013+met_name, 
                   data=tracts, sum)

AaronGullickson

## Reading in data adventures!

library(readr)
library(haven)
library(readxl)


# Reading in Text Files ---------------------------------------------------

#read in basic csv