15 Writing Methods & Results Reproducibly

How to use R functions and inline code to embed statistics in text

Author

Zihan Hei

Published

10.15.2025

Abstract

This chapter teaches researchers to write reproducible results sections by computing statistics in R and embedding them directly into manuscript text. Students learn a two-step process: (1) calculate statistics using R functions and store them as objects, and (2) insert those values into prose using Quarto’s inline code syntax. Through five practical examples, the chapter covers calculating sample sizes, computing percentages, formatting numbers as words, creating descriptive statistics tables, and running statistical tests. By replacing manually typed numbers with code-generated values, researchers eliminate transcription errors and create manuscripts that automatically update when data or analyses change, following reproducible research best practices.By the end of this chapter, researchers will be able to transform static numbers in their research papers into dynamic, code-generated values for research reproducibility.

Keywords

quarto publishing, in line coding, writing

Advanced Module

This is an advanced chapter and not required for your report or manuscript!

In reproducible research, writing numbers manually (e.g., “We surveyed 120 people.”) can lead to errors if you import data later (after you have collected 140 people). Instead, use R functions inside Quarto to turn your results directly into sentences!

15.1 Load Library

## need to run chunks with both regular r and webr-r versions for this page to work
#| label: setup-regular-r
#| include: false
#| message: false
#| warning: false

# Load packages for regular R chunks
library(dplyr)
library(tidyr)
library(psych)
library(tibble)
library(knitr)
library(scales)
library(english)
library(stringr)

select_data <- structure(list(
  AGE = c(29L, 40L, 23L, 35L, 67L, 45L, 20L, 34L, 
59L, 40L, 30L, 41L, 29L, 24L, 72L, 23L, 22L, 51L, NA, 36L, 59L, 
29L, 21L, 36L, 47L, 24L, 33L, 27L, 21L, 21L, 42L, 22L, 26L, 62L, 
35L, 29L, 30L, 20L, 42L, 33L, 35L, 33L, 35L, 45L, 33L, 40L, 58L, 
36L, 25L, 39L, 24L, 42L, 36L, 43L, 28L, 30L, 51L, 25L, 27L, 30L, 
54L, 33L, 52L, 52L, 20L, 22L, 32L, 22L, 25L, 28L, 19L, 27L, 31L, 
34L, 37L, 48L, 61L, 49L, 28L, 24L, 34L, 32L, 37L, 29L, 30L, 29L, 
43L, 73L, 37L, 21L, 31L, 56L, 25L, 54L, 54L, 37L, 59L, 30L, 19L, 
26L, 46L, 29L, 32L, 20L, 39L, 38L, 23L, 47L, 28L, 27L, 67L, 52L, 
22L, 27L, 44L, 48L, 36L, 28L, 21L, 56L, 52L, 38L), EDUCATION = c(6L, 
2L, 3L, 5L, 6L, 5L, 3L, 5L, 2L, 3L, 6L, 6L, 5L, 5L, 6L, 2L, 6L, 
5L, 6L, 5L, 5L, 5L, 5L, 5L, 6L, 3L, 2L, 5L, 5L, 3L, 6L, 5L, 3L, 
4L, 5L, 2L, 3L, 3L, 5L, 5L, 5L, 5L, 6L, 3L, 3L, 5L, 6L, 6L, 5L, 
5L, 2L, 6L, 4L, 6L, 5L, 6L, 6L, 5L, 3L, 5L, 6L, 6L, 4L, 6L, 6L, 
3L, 6L, 3L, 6L, 5L, 5L, 5L, 5L, 6L, 5L, 5L, 4L, 6L, 5L, 3L, 2L, 
6L, 6L, 4L, 6L, 6L, 5L, 6L, 6L, 5L, 6L, 3L, 2L, 5L, 6L, 6L, 5L, 
5L, 3L, 4L, 5L, 5L, 6L, 4L, 6L, 5L, 3L, 6L, 6L, 5L, 6L, 3L, 5L, 
5L, 3L, 6L, 6L, 3L, 3L, 5L, 5L, 5L), SOCIALSTATUS = c(6L, 3L, 
4L, 6L, 9L, 7L, 4L, 3L, 3L, 4L, 3L, 5L, 6L, 6L, 8L, 4L, 9L, 7L, 
6L, 4L, 4L, 4L, 6L, 4L, 7L, 6L, 3L, 6L, 5L, 8L, 7L, 5L, 5L, 5L, 
5L, 1L, 2L, 5L, 6L, 2L, 6L, 6L, 5L, 2L, 3L, 5L, 6L, 5L, 4L, 3L, 
2L, 7L, 7L, 8L, 3L, 6L, 8L, 5L, 5L, 5L, 7L, 7L, 8L, 5L, 6L, 1L, 
7L, 5L, 6L, 3L, 7L, 6L, 6L, 6L, 7L, 6L, 3L, 8L, 8L, 3L, 5L, 6L, 
6L, 1L, 6L, 4L, 6L, 6L, 7L, 5L, 6L, 4L, 3L, 3L, 9L, 6L, 7L, 5L, 
7L, 5L, 5L, 6L, 8L, 5L, 7L, 4L, 3L, 4L, 4L, 4L, 5L, 4L, 7L, 6L, 
3L, 6L, 6L, 7L, 7L, 5L, 6L, 8L), INCOME = c("$100,000-$149,999", 
"$25,000-$49,999", "Prefer not to say", "$150,000 or more", "$100,000-$149,999", 
"$150,000 or more", "$50,000-$74,999", "$25,000-$49,999", "Less than $25,000", 
"$100,000-$149,999", "Less than $25,000", "$25,000-$49,999", 
"$50,000-$74,999", "$100,000-$149,999", "$75,000-$99,999", "Less than $25,000", 
"$50,000-$74,999", "$75,000-$99,999", "Less than $25,000", "$100,000-$149,999", 
"$25,000-$49,999", "$100,000-$149,999", "$75,000-$99,999", "$100,000-$149,999", 
"$100,000-$149,999", "$25,000-$49,999", "$25,000-$49,999", "$100,000-$149,999", 
"$75,000-$99,999", "$50,000-$74,999", "$50,000-$74,999", "$50,000-$74,999", 
"$50,000-$74,999", "$50,000-$74,999", "$150,000 or more", "Prefer not to say", 
"Less than $25,000", "$25,000-$49,999", "$100,000-$149,999", 
"$50,000-$74,999", "$50,000-$74,999", "$100,000-$149,999", "$50,000-$74,999", 
"Less than $25,000", "$25,000-$49,999", "$75,000-$99,999", "$100,000-$149,999", 
"$25,000-$49,999", "$50,000-$74,999", "$50,000-$74,999", "$50,000-$74,999", 
"$75,000-$99,999", "$25,000-$49,999", "$100,000-$149,999", "$25,000-$49,999", 
"$50,000-$74,999", "$100,000-$149,999", "$25,000-$49,999", "$25,000-$49,999", 
"$150,000 or more", "$150,000 or more", "$50,000-$74,999", "$150,000 or more", 
"$100,000-$149,999", "$50,000-$74,999", "$50,000-$74,999", "$75,000-$99,999", 
"Less than $25,000", "$100,000-$149,999", "$25,000-$49,999", 
"Less than $25,000", "Less than $25,000", "$100,000-$149,999", 
"$100,000-$149,999", "$150,000 or more", "$50,000-$74,999", "Less than $25,000", 
"$50,000-$74,999", "$25,000-$49,999", "$100,000-$149,999", "$100,000-$149,999", 
"$100,000-$149,999", "$75,000-$99,999", "$25,000-$49,999", "$150,000 or more", 
"$75,000-$99,999", "$100,000-$149,999", "$100,000-$149,999", 
"$75,000-$99,999", "$100,000-$149,999", "$100,000-$149,999", 
"Less than $25,000", "$25,000-$49,999", "$25,000-$49,999", "$100,000-$149,999", 
"$100,000-$149,999", "$150,000 or more", "$25,000-$49,999", "$75,000-$99,999", 
"$75,000-$99,999", "$150,000 or more", "$100,000-$149,999", "$150,000 or more", 
"$100,000-$149,999", "$50,000-$74,999", "$100,000-$149,999", 
"$25,000-$49,999", "$50,000-$74,999", "$25,000-$49,999", "$25,000-$49,999", 
"$100,000-$149,999", "$25,000-$49,999", "$100,000-$149,999", 
"$25,000-$49,999", "$25,000-$49,999", "$100,000-$149,999", "$100,000-$149,999", 
"$75,000-$99,999", "$100,000-$149,999", "Less than $25,000", 
"$75,000-$99,999", "$100,000-$149,999"), RELIGIOUS_IDENTITY = c("1", 
"9", "9", "1", "1", "1", "1", "9", "8", "1", "1", "7", "1", "9", 
"1", "8", "1", "5,9", "1", "1", "8", "1", "1", "1", "1", "-99", 
"1", "1", "1", "9", "1", "1", "1", "9", "-99", "9", "9", "9", 
"9", "1", "1", "9", "1", "9", "1", "8", "9", "1", "9", "-99", 
"9", "1", "1", "1", "1", "1", "1", "1", "9", "9", "1", "1", "9", 
"1", "1", "9", "1", "1", "9", "1", "1", "9", "1", "9", "9", "9", 
"1", "1", "1", "1", "1", "9", "9", "9", "1", "1", "9", "6", "1", 
"1", "1", "1", "9", "2", "1", "9", "1", "9", "1", "2", "9", "1", 
"1", "9", "1", "1", "9", "4", "1", "9", "9", "1", "9", "9", "9", 
"9", "9", "9", "4", "1", "9", "1"), RACE = c("3", "7", "3,7", 
"2", "7", "3", "7", "7", "7", "7", "7", "8", "3", "3,7", "6", 
"3", "3", "7", "3", "7", "7", "3", "3", "2", "7", "3", "4", "7", 
"7", "2", "3", "2", "4", "1,7", "2", "2", "4,7", "4", "7", "4", 
"7", "7", "4", "7", "4", "2", "2", "7", "3", "7", "3,4,7", "7", 
"3", "3", "3", "7", "7", "3", "4", "2", "3", "7", "7", "3", "3", 
"7", "3", "7", "7", "7", "7", "5", "7", "3", "2", "7", "7", "7", 
"7", "2", "2,3", "7", "4", "3", "2", "3", "2,7", "7", "3", "3", 
"7", "3", "7", "7", "3", "2", "4", "2", "2", "2", "7", "3,6", 
"7", "2,7", "2", "7", "7", "2", "3", "7", "7", "7", "2", "2", 
"7", "2", "2", "7", "2", "1,7", "3", "7"), STREETRACE = c("Black", 
"White", NA, "Asian American", "White", "Black", "White", "White", 
"White", "White", "White", "Some other race", "Black", "Black", 
"White", "Black", "Black", "White", "Black", "White", "White", 
"Black", "Black", "Asian American", "Native American/American Indian", 
"Black", "Latine", "White", "White", "Asian American", "Black", 
"Asian American", "White", "White", "Asian American", "Mexican", 
"White", "Mexican", "White", "Mexican", "White", "White", "White", 
"White", "Latine", "Asian American", "Asian American", "White", 
"Black", "White", "Latine", "Latine", "Black", "Black", "Black", 
"White", "White", "Black", "Latine", "Asian American", "Black", 
"White", "White", "Black", "Black", "White", "Native American/American Indian", 
"White", "White", "White", "White", NA, "White", "Black", "Asian American", 
"White", "White", "White", "White", "Asian American", "Black", 
"White", "Latine", "Black", "Asian American", "Black", "White", 
"White", "Black", "Black", "White", "Black", "White", "White", 
"Black", "Asian American", "Latine", "Asian American", "Asian American", 
"Asian American", "White", "Black", "White", "White", "Asian American", 
"White", "White", "Mexican", "Black", "White", "White", "White", 
"Asian American", "Asian American", "White", "Asian American", 
"Asian American", "White", "Asian American", "Native American/American Indian", 
"Black", "White"), GENDER = c(2L, 2L, 2L, 1L, 2L, 1L, 1L, 2L, 
1L, 1L, 2L, 3L, 1L, 1L, 2L, 1L, 1L, 2L, 1L, 2L, 1L, 1L, 2L, 2L, 
1L, 1L, 1L, 1L, 1L, 2L, 1L, 2L, 1L, 1L, 2L, 3L, 3L, 2L, 2L, 2L, 
2L, 2L, 1L, 2L, 2L, 1L, 1L, 2L, 2L, 1L, 2L, 2L, 2L, 1L, 1L, 3L, 
1L, 1L, 2L, 1L, 2L, 1L, 1L, 2L, 2L, 1L, 1L, 1L, 2L, 1L, 1L, 2L, 
2L, 2L, 1L, 2L, 1L, 1L, 2L, 2L, 2L, 2L, 2L, 1L, 1L, 1L, 2L, 2L, 
2L, 2L, 1L, 1L, 1L, 1L, 2L, 2L, 1L, 2L, 2L, 1L, 1L, 2L, 2L, 1L, 
1L, 1L, 1L, 2L, 2L, 2L, 2L, 2L, 1L, 1L, 2L, 1L, 2L, 2L, 2L, 1L, 
2L, 1L), SEXUAL_IDENTITY = c("Bisexual, pansexual, or queer", 
"Straight or heterosexual", "Straight or heterosexual", "Straight or heterosexual", 
"Straight or heterosexual", "Straight or heterosexual", "Straight or heterosexual", 
"Straight or heterosexual", "Straight or heterosexual", "Straight or heterosexual", 
"Gay or lesbian", "Bisexual, pansexual, or queer", "Straight or heterosexual", 
"Gay or lesbian", "Straight or heterosexual", "Straight or heterosexual", 
"Gay or lesbian", "Straight or heterosexual", "Straight or heterosexual", 
"Straight or heterosexual", "Bisexual, pansexual, or queer", 
"Straight or heterosexual", "Straight or heterosexual", "Bisexual, pansexual, or queer", 
"Straight or heterosexual", "Bisexual, pansexual, or queer", 
"Straight or heterosexual", "Bisexual, pansexual, or queer", 
"Straight or heterosexual", "Straight or heterosexual", "Straight or heterosexual", 
"Straight or heterosexual", "Straight or heterosexual", "Straight or heterosexual", 
"Straight or heterosexual", "Asexual", "Not sure", "Straight or heterosexual", 
"Straight or heterosexual", "Straight or heterosexual", "Straight or heterosexual", 
"Bisexual, pansexual, or queer", "Straight or heterosexual", 
"Straight or heterosexual", "Straight or heterosexual", "Straight or heterosexual", 
"Straight or heterosexual", "Straight or heterosexual", "Bisexual, pansexual, or queer", 
"Bisexual, pansexual, or queer", "Straight or heterosexual", 
"Gay or lesbian", "Straight or heterosexual", "Bisexual, pansexual, or queer", 
"Gay or lesbian", "Asexual", "Bisexual, pansexual, or queer", 
"Bisexual, pansexual, or queer", "Straight or heterosexual", 
"Straight or heterosexual", "Straight or heterosexual", "Straight or heterosexual", 
"Straight or heterosexual", "Straight or heterosexual", "Straight or heterosexual", 
"Bisexual, pansexual, or queer", "Straight or heterosexual", 
"Straight or heterosexual", "Gay or lesbian", "Straight or heterosexual", 
"Gay or lesbian", "Straight or heterosexual", "Straight or heterosexual", 
"Straight or heterosexual", "Straight or heterosexual", "Straight or heterosexual", 
"Straight or heterosexual", "Asexual", "Straight or heterosexual", 
"Straight or heterosexual", "Straight or heterosexual", "Straight or heterosexual", 
"Bisexual, pansexual, or queer", "Bisexual, pansexual, or queer", 
"Straight or heterosexual", "Bisexual, pansexual, or queer", 
"Straight or heterosexual", "Straight or heterosexual", "Straight or heterosexual", 
"Straight or heterosexual", "Straight or heterosexual", "Straight or heterosexual", 
"Bisexual, pansexual, or queer", "Asexual", "Straight or heterosexual", 
"Straight or heterosexual", "Gay or lesbian", "Bisexual, pansexual, or queer", 
"Straight or heterosexual", "Straight or heterosexual", "Bisexual, pansexual, or queer", 
"Straight or heterosexual", "Straight or heterosexual", "Straight or heterosexual", 
"Straight or heterosexual", "Straight or heterosexual", "Bisexual, pansexual, or queer", 
"Straight or heterosexual", "Straight or heterosexual", "Straight or heterosexual", 
"Straight or heterosexual", "Bisexual, pansexual, or queer", 
"Bisexual, pansexual, or queer", "Straight or heterosexual", 
"Straight or heterosexual", "Straight or heterosexual", "Gay or lesbian", 
"Straight or heterosexual", "Straight or heterosexual", "Straight or heterosexual", 
"Gay or lesbian", "Straight or heterosexual"), POLITICALBELIEFS = c(4L, 
5L, 5L, 3L, 4L, 3L, 4L, 4L, NA, 6L, 4L, 3L, 3L, 1L, 6L, 2L, 2L, 
2L, 4L, 1L, 2L, 4L, 4L, 5L, 4L, 2L, 6L, 2L, NA, 3L, 3L, 4L, 3L, 
1L, 4L, 3L, 2L, 4L, 4L, 2L, 4L, 2L, 5L, 3L, 3L, 2L, 5L, 3L, 3L, 
3L, 5L, 6L, 5L, 5L, 6L, 5L, 5L, 4L, 5L, 3L, 5L, 5L, 3L, 5L, 5L, 
2L, 6L, 3L, 6L, 5L, 5L, 3L, 2L, 5L, 5L, 3L, 5L, 4L, 2L, 4L, 3L, 
6L, 4L, 1L, 5L, 3L, 3L, 3L, 6L, 4L, 6L, 3L, 3L, 1L, 5L, 5L, 5L, 
3L, 4L, 4L, 1L, 5L, 3L, 2L, 4L, 4L, 2L, 3L, 3L, 3L, 3L, 4L, 1L, 
4L, 3L, 4L, 2L, 5L, 5L, 4L, 3L, 2L), POLITICALAFFIL = c("Republican Party", 
"Republican Party", NA, "Democratic Party", NA, "Democratic Party", 
"Republican Party", "Republican Party", NA, NA, "Republican Party", 
"Democratic Party", "Democratic Party", "Democratic Party", "Conservative Party", 
"Democratic Party", "Republican Party", NA, "Republican Party", 
"Democratic Party", NA, "Libertarian Party", "Democratic Party", 
"Republican Party", "Republican Party", "Libertarian Party", 
"Republican Party", "Democratic Party", "Libertarian Party", 
"Democratic Party", "Libertarian Party", "Libertarian Party", 
"Democratic Party", "Democratic Party", "Socialist or Green Party", 
"Democratic Party", "Democratic Party", NA, "Libertarian Party", 
"Democratic Party", "Democratic Party", "Democratic Party", "Republican Party", 
"Democratic Party", NA, "Democratic Party", "Conservative Party", 
"Republican Party", "Democratic Party", "Democratic Party", "Republican Party", 
"Conservative Party", NA, "Republican Party", "Republican Party", 
"Republican Party", "Republican Party", "Democratic Party", "Republican Party", 
"Democratic Party", "Republican Party", "Democratic Party", "Democratic Party", 
"Conservative Party", "Republican Party", "Democratic Party", 
"Conservative Party", "Democratic Party", "Conservative Party", 
"Conservative Party", "Republican Party", "Democratic Party", 
"Democratic Party", "Republican Party", "Republican Party", "Democratic Party", 
"Republican Party", "Democratic Party", "Republican Party", NA, 
"Democratic Party", "Republican Party", NA, NA, "Republican Party", 
"Democratic Party", "Democratic Party", "Democratic Party", "Democratic Party", 
"Republican Party", "Conservative Party", "Democratic Party", 
"Democratic Party", "Democratic Party", "Democratic Party", "Republican Party", 
"Republican Party", "Democratic Party", NA, NA, "Democratic Party", 
"Conservative Party", "Democratic Party", "Democratic Party", 
"Republican Party", "Democratic Party", "Democratic Party", "Democratic Party", 
NA, "Democratic Party", "Democratic Party", NA, "Democratic Party", 
NA, "Libertarian Party", NA, "Democratic Party", "Libertarian Party", 
"Republican Party", NA, "Republican Party", "Democratic Party"
), VOTE2024 = c(1L, 1L, 8L, 2L, 2L, 1L, 1L, 8L, 8L, 1L, 1L, 2L, 
2L, 2L, 1L, 8L, 1L, 2L, 1L, 2L, 2L, NA, 2L, 2L, 1L, 1L, 1L, 2L, 
NA, 2L, 1L, 8L, 2L, 2L, 8L, 2L, 2L, 8L, 5L, 2L, 2L, 2L, 1L, 8L, 
2L, 2L, 1L, 1L, 2L, 2L, 8L, 1L, 7L, 1L, 1L, 1L, 1L, 1L, 1L, 2L, 
1L, 1L, 2L, 1L, 1L, 2L, 1L, 2L, 1L, 1L, 8L, 2L, 1L, 1L, 1L, 2L, 
1L, 1L, 1L, 8L, 2L, 1L, 2L, 2L, 1L, 2L, 2L, 2L, 1L, 1L, 1L, 2L, 
8L, 2L, 1L, 1L, 1L, 2L, 8L, 8L, 2L, 1L, 2L, 2L, 1L, 1L, 2L, 2L, 
NA, 2L, 2L, 2L, 2L, 8L, 8L, 2L, 2L, 1L, 1L, 1L, 1L, 2L), SERIOUS = c("Yes", 
"Yes", "Yes", "Yes", "Yes", "Yes", "Yes", "Yes", "Yes", "Yes", 
"Yes", "Yes", "Yes", "Yes", "Yes", "Yes", "Yes", "Yes", "Yes", 
NA, "Yes", "Yes", "Yes", "Yes", "Yes", "Yes", "Yes", "Yes", "Yes", 
"Yes", "Yes", "Yes", "Yes", "Yes", "Yes", "Yes", "Yes", "Yes", 
"Yes", "Yes", "Yes", "Yes", "Yes", "Yes", "Yes", "Yes", "Yes", 
"Yes", "Yes", "Yes", "Yes", "Yes", "Yes", "Yes", "Yes", "Yes", 
"Yes", "Yes", "Yes", "Yes", "Yes", "Yes", "Yes", "Yes", "Yes", 
"Yes", "Yes", "Yes", "Yes", "Yes", "Yes", "Yes", "Yes", "Yes", 
"Yes", "Yes", "Yes", "Yes", "Yes", "Yes", "Yes", "Yes", "Yes", 
"Yes", "Yes", "Yes", "Yes", "Yes", "Yes", "Yes", "Yes", "Yes", 
"Yes", "Yes", "Yes", "Yes", "Yes", "Yes", "Yes", "Yes", "Yes", 
"Yes", "Yes", "Yes", "Yes", "Yes", "Yes", "Yes", "Yes", "Yes", 
"Yes", "Yes", "Yes", "Yes", "Yes", "Yes", "Yes", "Yes", "Yes", 
"Yes", "Yes", "Yes"), POLITICALPARTY = c("Republican", "Republican", 
"Independent", "Democrat", "Independent", "Democrat", "Republican", 
"Republican", "Independent", "Independent", "Republican", "Independent", 
"Democrat", "Democrat", "Republican", "Republican", "Republican", 
"Independent", "Independent", "Democrat", "Independent", "Independent", 
"Democrat", "Republican", "Republican", "Democrat", "Republican", 
"Democrat", "Democrat", "Democrat", "Independent", "Independent", 
"Democrat", "Democrat", "Independent", "Independent", "Democrat", 
"Independent", "Independent", "Democrat", "Independent", "Democrat", 
"Independent", "Independent", "Independent", "Democrat", "Republican", 
"Republican", "Democrat", "Democrat", "Republican", "Republican", 
"Independent", "Republican", "Republican", "Republican", "Republican", 
"Democrat", "Republican", "Democrat", "Republican", "Democrat", 
"Democrat", "Republican", "Republican", "Independent", "Republican", 
"Independent", "Republican", "Republican", "Republican", "Democrat", 
"Democrat", "Republican", "Republican", "Democrat", "Republican", 
"Republican", "Republican", "Independent", "Independent", "Republican", 
"Independent", "Independent", "Republican", "Democrat", "Democrat", 
"Democrat", "Democrat", "Independent", "Independent", "Independent", 
"Democrat", "Democrat", "Democrat", "Republican", "Republican", 
"Democrat", "Independent", "Independent", "Democrat", "Republican", 
"Democrat", "Democrat", "Republican", "Independent", "Independent", 
"Democrat", "Independent", "Democrat", "Democrat", "Independent", 
"Democrat", "Independent", "Independent", "Independent", "Democrat", 
"Independent", "Republican", "Independent", "Democrat", "Democrat"
), SEX = c("Male", "Male", "Male", "Female", "Male", "Female", 
"Female", "Male", "Female", "Female", "Male", "Female", "Female", 
"Female", "Male", "Female", "Female", "Male", "Female", "Male", 
"Female", "Male", "Male", "Male", "Female", "Female", "Female", 
"Female", "Female", "Male", "Female", "Male", "Female", "Female", 
"Male", "Female", "Male", "Male", "Male", "Male", "Male", "Male", 
"Female", "Male", "Male", "Female", "Female", "Male", "Male", 
"Female", "Male", "Male", "Male", "Female", "Female", "Male", 
"Female", "Female", "Male", "Female", "Male", "Female", "Female", 
"Male", "Male", "Female", "Female", "Female", "Male", "Female", 
"Female", "Male", "Male", "Male", "Female", "Male", "Female", 
"Female", "Male", "Male", "Male", "Male", "Male", "Female", "Female", 
"Female", "Male", "Male", "Male", "Male", "Female", "Female", 
"Female", "Female", "Male", "Male", "Female", "Male", "Male", 
"Female", "Female", "Male", "Male", "Female", "Female", "Female", 
"Female", "Male", "Male", "Male", "Male", "Male", "Female", "Female", 
"Male", "Female", "Male", "Male", "Male", "Female", "Male", "Female"
), ETHNICITY = c("Black", "White", "Mixed/Other", "Asian", "White", 
"Black", "White", "Mixed/Other", "White", "White", "White", "Mixed/Other", 
"Black", "Mixed/Other", "White", "Black", "Black", "White", "Black", 
"White", "White", "Black", "Black", "Asian", "White", "Black", 
"Mixed/Other", "White", "White", "Asian", "Black", "Asian", "Mixed/Other", 
"White", "Asian", "Asian", "White", "White", "White", "Mixed/Other", 
"White", "Mixed/Other", "Mixed/Other", "White", "Mixed/Other", 
"Asian", "Asian", "White", "Black", "White", "Mixed/Other", "White", 
"Black", "Black", "Mixed/Other", "White", "White", "Black", "Mixed/Other", 
"Asian", "Black", "White", "White", "Black", "Black", "Mixed/Other", 
"Black", "White", "White", "White", "White", "Mixed/Other", "White", 
"Mixed/Other", "Asian", "White", "White", "White", "White", "Asian", 
"Mixed/Other", "Asian", "Mixed/Other", "Black", "Asian", "Mixed/Other", 
"Mixed/Other", "White", "Black", "Black", "White", "Black", "White", 
"White", "Black", "Asian", "Mixed/Other", "Asian", "Asian", "Asian", 
"White", "Mixed/Other", "White", "Mixed/Other", "Asian", "White", 
"White", "Asian", "Black", "White", "White", "White", "Asian", 
"Asian", "White", "Asian", "Asian", "White", "Asian", "Mixed/Other", 
"Black", "Mixed/Other"), Nationality = c("United States", "United States", 
"United States", "United States", "United States", "United States", 
"United States", "United States", "United States", "United States", 
"United States", "United States", "United States", "United States", 
"United States", "United States", "United States", "United States", 
"United States", "United States", "United States", "United States", 
"United States", "United States", "United States", "United States", 
"United States", "United States", "United States", "United States", 
"United States", "United States", "United States", "United States", 
"United States", "United States", "United States", "United States", 
"United States", "United States", "United States", "United States", 
"United States", "United States", "United States", "United States", 
"United States", "United States", "United States", "United States", 
"United States", "United States", "United States", "United States", 
"United States", "United States", "United States", "United States", 
"United States", "United States", "United States", "United States", 
"United States", "United States", "United States", "United States", 
"United States", "United States", "United States", "United States", 
"United States", "United States", "United States", "United States", 
"United States", "United States", "United States", "United States", 
"United States", "United States", "United States", "United States", 
"United States", "United States", "United States", "United States", 
"United States", "United States", "United States", "United States", 
"United States", "United States", "United States", "United States", 
"United States", "United States", "United States", "United States", 
"United States", "United States", "United States", "United States", 
"United States", "United States", "United States", "United States", 
"United States", "United States", "United States", "United States", 
"United States", "United States", "United States", "United States", 
"United States", "United States", "United States", "United States", 
"United States", "United States", "United States", "United States"
), Student.status = c("Yes", "No", "Yes", "No", "No", "No", "Yes", 
"DATA_EXPIRED", "DATA_EXPIRED", "Yes", "No", "No", "No", "DATA_EXPIRED", 
"DATA_EXPIRED", "DATA_EXPIRED", "No", "No", "DATA_EXPIRED", "No", 
"No", "No", "Yes", "No", "No", "No", "No", "Yes", "No", "DATA_EXPIRED", 
"No", "Yes", "No", "No", "DATA_EXPIRED", "No", "No", "No", "No", 
"No", "No", "Yes", "Yes", "DATA_EXPIRED", "Yes", "No", "DATA_EXPIRED", 
"No", "No", "No", "No", "Yes", "No", "Yes", "No", "Yes", "No", 
"No", "No", "DATA_EXPIRED", "No", "No", "No", "DATA_EXPIRED", 
"No", "No", "No", "Yes", "No", "Yes", "Yes", "Yes", "No", "DATA_EXPIRED", 
"No", "No", "No", "No", "No", "No", "No", "No", "No", "Yes", 
"Yes", "Yes", "No", "No", "Yes", "No", "Yes", "No", "No", "DATA_EXPIRED", 
"No", "No", "Yes", "No", "Yes", "DATA_EXPIRED", "No", "DATA_EXPIRED", 
"No", "Yes", "No", "DATA_EXPIRED", "Yes", "No", "Yes", "Yes", 
"No", "No", "No", "No", "No", "No", "No", "No", "Yes", "No", 
"DATA_EXPIRED", "Yes"), Employment.status = c("Part-Time", "Unemployed (and job seeking)", 
"DATA_EXPIRED", "Full-Time", "Not in paid work (e.g. homemaker', 'retired or disabled)", 
"Full-Time", "Part-Time", "DATA_EXPIRED", "DATA_EXPIRED", "Full-Time", 
"Part-Time", "Full-Time", "Full-Time", "DATA_EXPIRED", "Full-Time", 
"DATA_EXPIRED", "Part-Time", "Full-Time", "Part-Time", "Full-Time", 
"DATA_EXPIRED", "Full-Time", "Full-Time", "Part-Time", "Full-Time", 
"Full-Time", "Not in paid work (e.g. homemaker', 'retired or disabled)", 
"Full-Time", "Not in paid work (e.g. homemaker', 'retired or disabled)", 
"Part-Time", "Part-Time", "DATA_EXPIRED", "Full-Time", "Unemployed (and job seeking)", 
"DATA_EXPIRED", "Unemployed (and job seeking)", "Unemployed (and job seeking)", 
"Other", "Full-Time", "Full-Time", "Part-Time", "Full-Time", 
"Full-Time", "DATA_EXPIRED", "Part-Time", "Full-Time", "Full-Time", 
"Part-Time", "Full-Time", "Part-Time", "Unemployed (and job seeking)", 
"Part-Time", "Unemployed (and job seeking)", "Part-Time", "Full-Time", 
"Part-Time", "Part-Time", "Full-Time", "Full-Time", "DATA_EXPIRED", 
"Full-Time", "Part-Time", "Not in paid work (e.g. homemaker', 'retired or disabled)", 
"Full-Time", "DATA_EXPIRED", "Not in paid work (e.g. homemaker', 'retired or disabled)", 
"Part-Time", "DATA_EXPIRED", "Full-Time", "Part-Time", "Part-Time", 
"Part-Time", "Full-Time", "Full-Time", "Due to start a new job within the next month", 
"Full-Time", "Not in paid work (e.g. homemaker', 'retired or disabled)", 
"Part-Time", "Part-Time", "Unemployed (and job seeking)", "Full-Time", 
"Full-Time", "Full-Time", "Unemployed (and job seeking)", "Full-Time", 
"Part-Time", "DATA_EXPIRED", "Other", "Unemployed (and job seeking)", 
"Full-Time", "Full-Time", "Part-Time", "Unemployed (and job seeking)", 
"Not in paid work (e.g. homemaker', 'retired or disabled)", "Part-Time", 
"Full-Time", "Full-Time", "Full-Time", "Not in paid work (e.g. homemaker', 'retired or disabled)", 
"DATA_EXPIRED", "Part-Time", "Full-Time", "Full-Time", "DATA_EXPIRED", 
"Part-Time", "DATA_EXPIRED", "Other", "Part-Time", "Full-Time", 
"Full-Time", "Full-Time", "Not in paid work (e.g. homemaker', 'retired or disabled)", 
"Full-Time", "Not in paid work (e.g. homemaker', 'retired or disabled)", 
"Full-Time", "Full-Time", "Full-Time", "Full-Time", "Unemployed (and job seeking)", 
"Unemployed (and job seeking)", "DATA_EXPIRED", "Full-Time"), 
    ZEROSUM_1 = c(4L, 5L, 7L, 2L, 1L, 6L, 5L, 6L, 6L, 4L, 2L, 
    1L, 4L, 3L, 3L, 6L, 2L, 2L, 4L, 5L, 1L, 6L, 4L, 4L, 2L, 6L, 
    6L, 4L, 5L, 4L, 6L, 2L, 5L, 4L, 6L, 4L, 1L, 2L, 5L, 1L, 2L, 
    1L, 5L, 5L, 4L, 3L, 5L, 2L, 3L, 6L, 6L, 4L, 1L, 7L, 5L, 7L, 
    5L, 5L, 1L, 4L, 5L, 6L, 1L, 3L, 2L, 7L, 7L, 5L, 3L, 3L, 5L, 
    4L, 5L, 6L, 1L, 6L, 1L, 3L, 5L, 3L, 5L, 5L, 5L, 1L, 6L, 1L, 
    3L, 4L, 5L, 5L, 5L, 2L, 5L, 7L, 6L, 4L, 4L, 6L, 2L, 4L, 1L, 
    5L, 3L, 3L, 4L, 5L, 1L, 6L, 5L, 1L, 1L, 5L, 5L, 1L, 2L, 3L, 
    4L, 3L, 4L, 3L, 5L, 5L), ZEROSUM_2 = c(3L, 7L, 5L, 7L, 5L, 
    5L, 5L, 7L, 6L, 5L, 3L, 5L, 5L, 6L, 3L, 7L, 6L, 5L, 4L, 7L, 
    7L, 1L, 4L, 4L, 5L, 6L, 4L, 4L, 7L, 4L, 6L, 2L, 5L, 5L, 7L, 
    5L, 4L, 3L, 5L, 1L, 6L, 6L, 4L, 6L, 5L, 7L, 3L, 4L, 3L, 6L, 
    5L, 4L, 1L, 6L, 3L, 7L, 7L, 6L, 2L, 4L, 7L, 5L, 4L, 4L, 3L, 
    7L, 5L, 5L, 5L, 5L, 6L, 3L, 5L, 2L, 1L, 7L, 2L, 2L, 6L, 5L, 
    5L, 4L, 6L, 5L, 5L, 6L, 5L, 4L, 6L, 5L, 5L, NA, 5L, 7L, 5L, 
    4L, 4L, 7L, 4L, 4L, 7L, 4L, 3L, 2L, 6L, 7L, 7L, 6L, 4L, 5L, 
    2L, 5L, 7L, 1L, 4L, 4L, 4L, 5L, 4L, 3L, 5L, 5L), ZEROSUM_3 = c(5L, 
    5L, 5L, 6L, 5L, 3L, 6L, 7L, 4L, 5L, 5L, 4L, 4L, 7L, 4L, 5L, 
    5L, 7L, 3L, 7L, 7L, 6L, 4L, 3L, 5L, 6L, 4L, 2L, 6L, 4L, 6L, 
    2L, 6L, 4L, 7L, 5L, 5L, 6L, 5L, 7L, 6L, 6L, 4L, 6L, 4L, 7L, 
    5L, 2L, 6L, 6L, 6L, 5L, 1L, 6L, 5L, 7L, 6L, 1L, 6L, 5L, 4L, 
    3L, 5L, 2L, 4L, 7L, 5L, 5L, 5L, 4L, 7L, 4L, 5L, 3L, 1L, 7L, 
    5L, 5L, 6L, 5L, 4L, 5L, 5L, 7L, 5L, 6L, 7L, 4L, 5L, 5L, 5L, 
    NA, 6L, 7L, 5L, 4L, 4L, 7L, 3L, 4L, 7L, 6L, 5L, 2L, 4L, 6L, 
    7L, 4L, 4L, 7L, 6L, 5L, 5L, 2L, 7L, 5L, 4L, 2L, 4L, 3L, 4L, 
    4L), ZEROSUM_4 = c(4L, 4L, 7L, 1L, 1L, 5L, 4L, 4L, 4L, 4L, 
    4L, 1L, 2L, 2L, 3L, 1L, 3L, 2L, 4L, 1L, 1L, 5L, 4L, 5L, 1L, 
    5L, 6L, 4L, 3L, 3L, 3L, 2L, 3L, 4L, 5L, 3L, 1L, 1L, 2L, 1L, 
    2L, 1L, 5L, 4L, 4L, 1L, 2L, 4L, 1L, 3L, 6L, 4L, 1L, 5L, 4L, 
    7L, 4L, 1L, 6L, 3L, 5L, 6L, 1L, 3L, 3L, 1L, 2L, 1L, 5L, 3L, 
    5L, 3L, 4L, 2L, 1L, 5L, 3L, 3L, 6L, 3L, 1L, 6L, 2L, 1L, 6L, 
    3L, 3L, 1L, 5L, 4L, 6L, NA, 5L, 1L, 4L, 1L, 2L, 1L, 3L, 4L, 
    1L, 4L, 5L, 1L, 3L, 1L, 1L, 1L, 5L, 1L, 1L, 5L, 1L, 2L, 2L, 
    3L, 1L, 3L, 4L, 3L, 4L, 5L), ZEROSUM_5 = c(4L, 3L, 3L, 1L, 
    1L, 2L, 5L, 5L, 4L, 4L, 4L, 1L, 1L, 1L, 3L, 1L, 3L, 2L, 1L, 
    1L, 1L, 1L, 4L, 1L, 1L, 6L, 4L, 3L, 5L, 3L, 5L, 1L, 3L, 1L, 
    1L, 2L, 1L, 1L, 2L, 1L, 2L, 1L, 7L, 3L, 5L, 1L, 3L, 4L, 1L, 
    3L, 6L, 5L, 1L, 6L, 3L, 3L, 6L, 1L, 1L, 1L, 1L, 5L, 1L, 3L, 
    4L, 1L, 4L, 4L, 5L, 4L, 3L, 3L, 4L, 2L, 4L, 1L, 3L, 4L, 6L, 
    3L, 1L, 7L, 3L, 1L, 6L, 3L, 2L, 1L, 4L, 4L, 5L, 1L, 3L, 1L, 
    6L, 2L, 3L, 1L, 6L, 4L, 1L, 6L, 3L, 1L, 3L, 1L, 1L, 2L, 4L, 
    1L, 1L, 2L, 1L, 2L, 1L, 3L, 1L, 3L, 4L, 4L, 6L, 6L), ZEROSUM_6 = c(5L, 
    6L, 7L, 1L, 1L, 5L, 5L, 7L, 4L, 7L, 4L, 1L, 4L, 1L, 4L, 7L, 
    3L, 1L, 5L, 1L, 1L, 1L, 4L, 1L, 1L, 6L, 7L, 3L, 2L, 4L, 6L, 
    2L, 3L, 1L, 6L, 4L, 1L, 1L, 2L, 1L, 6L, 1L, 6L, 6L, 5L, 1L, 
    4L, 4L, 1L, 3L, 7L, 6L, 1L, 6L, 4L, 6L, 6L, 2L, 5L, 2L, 6L, 
    5L, 1L, 2L, 3L, 1L, 6L, 2L, 5L, 3L, 5L, 3L, 5L, 2L, 7L, 1L, 
    4L, 5L, 6L, 3L, 7L, 6L, 2L, 1L, 5L, 5L, 1L, 1L, 3L, 5L, 5L, 
    NA, 1L, 1L, 6L, 1L, 3L, 1L, 4L, 4L, 1L, 2L, 5L, 1L, 4L, 1L, 
    1L, 3L, 4L, 1L, 1L, 3L, 1L, 6L, 1L, 3L, 1L, 7L, 3L, 4L, 3L, 
    4L), ZEROSUM_7 = c(4L, 4L, 7L, 2L, 5L, 4L, 4L, 5L, 2L, 7L, 
    5L, 1L, 2L, 1L, 4L, 2L, 4L, 2L, 1L, 1L, 6L, 1L, 5L, 1L, 2L, 
    5L, 7L, 2L, 3L, NA, 5L, 1L, 3L, 1L, 1L, 4L, 3L, 4L, 5L, 1L, 
    6L, 1L, 4L, 5L, 5L, 2L, 5L, 4L, 1L, 3L, 4L, 6L, 1L, 5L, 3L, 
    2L, 6L, 1L, 5L, 1L, 5L, 4L, 4L, 4L, 5L, 4L, 5L, 4L, 4L, 4L, 
    3L, 3L, 5L, 3L, 7L, 1L, 7L, 3L, 5L, 3L, 5L, 6L, 1L, 1L, 6L, 
    2L, 5L, 5L, 4L, 4L, 4L, NA, 5L, 1L, 3L, 4L, 2L, 1L, 5L, 4L, 
    1L, 4L, 5L, 2L, 3L, 2L, 1L, 6L, 4L, 1L, 1L, 2L, 1L, 2L, 5L, 
    4L, 4L, 7L, 5L, 7L, 3L, 5L), ZEROSUM_8 = c(5L, 4L, 3L, 2L, 
    1L, 2L, 5L, 7L, 1L, 3L, 1L, 1L, 3L, 2L, 4L, 1L, 4L, 1L, 4L, 
    1L, 1L, 5L, 5L, 1L, 6L, 6L, 4L, 1L, 3L, 3L, 4L, 1L, 5L, 1L, 
    1L, 1L, 1L, 1L, 4L, 1L, 2L, 1L, 4L, 2L, 5L, 1L, 5L, 4L, 1L, 
    3L, 3L, 4L, 5L, 5L, 4L, 3L, 5L, 1L, 5L, 4L, 4L, 4L, 2L, 3L, 
    3L, 1L, 6L, 1L, 5L, 3L, 3L, 3L, 4L, 3L, 1L, 1L, 3L, 3L, 5L, 
    3L, 3L, 7L, 1L, 1L, 5L, 3L, 5L, 1L, 4L, 4L, 4L, NA, 2L, 1L, 
    4L, 3L, 1L, 1L, 4L, 4L, 1L, 3L, 3L, 2L, 3L, 1L, 1L, 3L, 4L, 
    1L, 1L, 2L, 1L, 6L, 1L, 3L, 4L, 2L, 4L, 3L, 4L, 5L), ZEROSUM_9 = c(3L, 
    5L, 4L, 1L, 1L, 6L, 7L, 4L, 4L, 6L, 1L, 1L, 4L, 1L, 4L, 5L, 
    6L, 1L, 4L, 1L, 1L, 1L, 4L, 1L, 1L, 2L, 5L, 3L, 3L, 3L, 2L, 
    1L, 3L, 1L, 2L, 1L, 1L, 1L, 2L, 1L, 2L, 1L, 4L, 1L, 4L, 1L, 
    3L, 1L, 1L, 3L, 5L, 5L, 1L, 5L, 2L, 2L, 6L, 1L, 2L, 1L, 7L, 
    4L, 1L, 3L, 4L, 1L, 4L, 1L, 6L, 3L, 3L, 1L, 4L, 5L, 1L, 1L, 
    1L, 2L, 5L, 3L, 1L, 5L, 1L, 1L, 4L, 1L, 1L, 1L, 3L, 2L, 5L, 
    NA, 1L, 1L, 5L, 2L, 3L, 1L, 3L, 4L, 1L, 7L, 3L, 1L, 1L, 1L, 
    1L, 2L, 5L, 1L, 1L, 2L, 1L, 2L, 1L, 3L, 1L, 1L, 2L, 3L, 4L, 
    5L), ZEROSUM_10 = c(5L, 4L, 6L, 1L, 1L, 3L, 5L, 5L, 4L, 5L, 
    5L, 1L, 1L, 1L, 4L, 5L, 6L, 2L, 1L, 1L, 1L, 1L, 4L, 1L, 1L, 
    6L, 4L, 4L, 1L, 4L, 5L, 1L, 4L, 1L, 3L, 3L, 4L, 3L, 3L, 1L, 
    2L, 2L, 5L, 2L, 5L, 3L, 3L, 4L, 1L, 3L, 2L, 5L, 1L, 6L, 6L, 
    4L, 7L, 1L, 5L, 2L, 4L, 4L, 1L, 3L, 4L, 1L, 5L, 5L, 5L, 3L, 
    3L, 3L, 4L, 6L, 6L, 1L, 5L, 3L, 5L, 3L, 4L, 6L, 1L, 1L, 6L, 
    3L, 3L, 2L, 4L, 4L, 6L, 1L, 2L, 1L, 4L, 3L, 3L, 1L, 2L, 4L, 
    1L, 6L, 3L, 2L, 3L, 1L, 1L, 5L, 3L, 1L, 1L, 2L, 1L, 6L, 1L, 
    3L, 2L, 5L, 5L, 3L, 4L, 6L), ZEROSUM_11 = c(5L, 3L, 2L, 2L, 
    4L, 4L, 4L, 5L, 4L, 4L, 3L, 1L, 1L, 1L, 3L, 4L, 7L, 2L, 4L, 
    4L, 1L, 1L, 4L, 5L, 1L, 5L, 6L, 4L, 1L, 4L, 5L, 1L, 3L, 1L, 
    2L, 3L, 1L, 4L, 4L, 1L, 2L, 1L, 6L, 1L, 5L, 1L, 4L, 2L, 1L, 
    3L, 5L, 6L, 1L, 6L, 2L, 6L, 6L, 1L, 2L, 2L, 5L, 6L, 2L, 2L, 
    2L, 1L, 5L, 4L, 5L, 4L, 4L, 2L, 4L, 4L, 5L, 1L, 3L, 5L, 6L, 
    3L, 7L, 6L, 1L, 1L, 6L, 6L, 4L, 4L, 3L, 2L, 5L, NA, 2L, 1L, 
    3L, 1L, 3L, 1L, 3L, 4L, 1L, 2L, 3L, 2L, 3L, 1L, 1L, 4L, 4L, 
    1L, 1L, 2L, 1L, 6L, 3L, 4L, 2L, 6L, 3L, 3L, 3L, 4L), EDUCATION_LEVEL = c("Graduate or professional degree", 
    "High school diploma or GED", "Some college, but no degree", 
    "Bachelor’s degree", "Graduate or professional degree", 
    "Bachelor’s degree", "Some college, but no degree", "Bachelor’s degree", 
    "High school diploma or GED", "Some college, but no degree", 
    "Graduate or professional degree", "Graduate or professional degree", 
    "Bachelor’s degree", "Bachelor’s degree", "Graduate or professional degree", 
    "High school diploma or GED", "Graduate or professional degree", 
    "Bachelor’s degree", "Graduate or professional degree", 
    "Bachelor’s degree", "Bachelor’s degree", "Bachelor’s degree", 
    "Bachelor’s degree", "Bachelor’s degree", "Graduate or professional degree", 
    "Some college, but no degree", "High school diploma or GED", 
    "Bachelor’s degree", "Bachelor’s degree", "Some college, but no degree", 
    "Graduate or professional degree", "Bachelor’s degree", 
    "Some college, but no degree", "Associates or technical degree", 
    "Bachelor’s degree", "High school diploma or GED", "Some college, but no degree", 
    "Some college, but no degree", "Bachelor’s degree", "Bachelor’s degree", 
    "Bachelor’s degree", "Bachelor’s degree", "Graduate or professional degree", 
    "Some college, but no degree", "Some college, but no degree", 
    "Bachelor’s degree", "Graduate or professional degree", 
    "Graduate or professional degree", "Bachelor’s degree", 
    "Bachelor’s degree", "High school diploma or GED", "Graduate or professional degree", 
    "Associates or technical degree", "Graduate or professional degree", 
    "Bachelor’s degree", "Graduate or professional degree", 
    "Graduate or professional degree", "Bachelor’s degree", 
    "Some college, but no degree", "Bachelor’s degree", "Graduate or professional degree", 
    "Graduate or professional degree", "Associates or technical degree", 
    "Graduate or professional degree", "Graduate or professional degree", 
    "Some college, but no degree", "Graduate or professional degree", 
    "Some college, but no degree", "Graduate or professional degree", 
    "Bachelor’s degree", "Bachelor’s degree", "Bachelor’s degree", 
    "Bachelor’s degree", "Graduate or professional degree", 
    "Bachelor’s degree", "Bachelor’s degree", "Associates or technical degree", 
    "Graduate or professional degree", "Bachelor’s degree", 
    "Some college, but no degree", "High school diploma or GED", 
    "Graduate or professional degree", "Graduate or professional degree", 
    "Associates or technical degree", "Graduate or professional degree", 
    "Graduate or professional degree", "Bachelor’s degree", 
    "Graduate or professional degree", "Graduate or professional degree", 
    "Bachelor’s degree", "Graduate or professional degree", 
    "Some college, but no degree", "High school diploma or GED", 
    "Bachelor’s degree", "Graduate or professional degree", 
    "Graduate or professional degree", "Bachelor’s degree", 
    "Bachelor’s degree", "Some college, but no degree", "Associates or technical degree", 
    "Bachelor’s degree", "Bachelor’s degree", "Graduate or professional degree", 
    "Associates or technical degree", "Graduate or professional degree", 
    "Bachelor’s degree", "Some college, but no degree", "Graduate or professional degree", 
    "Graduate or professional degree", "Bachelor’s degree", 
    "Graduate or professional degree", "Some college, but no degree", 
    "Bachelor’s degree", "Bachelor’s degree", "Some college, but no degree", 
    "Graduate or professional degree", "Graduate or professional degree", 
    "Some college, but no degree", "Some college, but no degree", 
    "Bachelor’s degree", "Bachelor’s degree", "Bachelor’s degree"
    ), RELIGIOUS_Identity = c("Christian", "Religiously Unaffiliated", 
    "Religiously Unaffiliated", "Christian", "Christian", "Christian", 
    "Christian", "Religiously Unaffiliated", "Other", "Christian", 
    "Christian", "Folk Religion", "Christian", "Religiously Unaffiliated", 
    "Christian", "Other", "Christian", NA, "Christian", "Christian", 
    "Other", "Christian", "Christian", "Christian", "Christian", 
    "Decline to answer", "Christian", "Christian", "Christian", 
    "Religiously Unaffiliated", "Christian", "Christian", "Christian", 
    "Religiously Unaffiliated", "Decline to answer", "Religiously Unaffiliated", 
    "Religiously Unaffiliated", "Religiously Unaffiliated", "Religiously Unaffiliated", 
    "Christian", "Christian", "Religiously Unaffiliated", "Christian", 
    "Religiously Unaffiliated", "Christian", "Other", "Religiously Unaffiliated", 
    "Christian", "Religiously Unaffiliated", "Decline to answer", 
    "Religiously Unaffiliated", "Christian", "Christian", "Christian", 
    "Christian", "Christian", "Christian", "Christian", "Religiously Unaffiliated", 
    "Religiously Unaffiliated", "Christian", "Christian", "Religiously Unaffiliated", 
    "Christian", "Christian", "Religiously Unaffiliated", "Christian", 
    "Christian", "Religiously Unaffiliated", "Christian", "Christian", 
    "Religiously Unaffiliated", "Christian", "Religiously Unaffiliated", 
    "Religiously Unaffiliated", "Religiously Unaffiliated", "Christian", 
    "Christian", "Christian", "Christian", "Christian", "Religiously Unaffiliated", 
    "Religiously Unaffiliated", "Religiously Unaffiliated", "Christian", 
    "Christian", "Religiously Unaffiliated", "Jewish", "Christian", 
    "Christian", "Christian", "Christian", "Religiously Unaffiliated", 
    "Muslim", "Christian", "Religiously Unaffiliated", "Christian", 
    "Religiously Unaffiliated", "Christian", "Muslim", "Religiously Unaffiliated", 
    "Christian", "Christian", "Religiously Unaffiliated", "Christian", 
    "Christian", "Religiously Unaffiliated", "Hindu", "Christian", 
    "Religiously Unaffiliated", "Religiously Unaffiliated", "Christian", 
    "Religiously Unaffiliated", "Religiously Unaffiliated", "Religiously Unaffiliated", 
    "Religiously Unaffiliated", "Religiously Unaffiliated", "Religiously Unaffiliated", 
    "Hindu", "Christian", "Religiously Unaffiliated", "Christian"
    ), VOTE_2024 = c("Donald Trump", "Donald Trump", "DID NOT VOTE IN 2024", 
    "Kamala Harris", "Kamala Harris", "Donald Trump", "Donald Trump", 
    "DID NOT VOTE IN 2024", "DID NOT VOTE IN 2024", "Donald Trump", 
    "Donald Trump", "Kamala Harris", "Kamala Harris", "Kamala Harris", 
    "Donald Trump", "DID NOT VOTE IN 2024", "Donald Trump", "Kamala Harris", 
    "Donald Trump", "Kamala Harris", "Kamala Harris", NA, "Kamala Harris", 
    "Kamala Harris", "Donald Trump", "Donald Trump", "Donald Trump", 
    "Kamala Harris", NA, "Kamala Harris", "Donald Trump", "DID NOT VOTE IN 2024", 
    "Kamala Harris", "Kamala Harris", "DID NOT VOTE IN 2024", 
    "Kamala Harris", "Kamala Harris", "DID NOT VOTE IN 2024", 
    "Chase Oliver", "Kamala Harris", "Kamala Harris", "Kamala Harris", 
    "Donald Trump", "DID NOT VOTE IN 2024", "Kamala Harris", 
    "Kamala Harris", "Donald Trump", "Donald Trump", "Kamala Harris", 
    "Kamala Harris", "DID NOT VOTE IN 2024", "Donald Trump", 
    "Cornel West", "Donald Trump", "Donald Trump", "Donald Trump", 
    "Donald Trump", "Donald Trump", "Donald Trump", "Kamala Harris", 
    "Donald Trump", "Donald Trump", "Kamala Harris", "Donald Trump", 
    "Donald Trump", "Kamala Harris", "Donald Trump", "Kamala Harris", 
    "Donald Trump", "Donald Trump", "DID NOT VOTE IN 2024", "Kamala Harris", 
    "Donald Trump", "Donald Trump", "Donald Trump", "Kamala Harris", 
    "Donald Trump", "Donald Trump", "Donald Trump", "DID NOT VOTE IN 2024", 
    "Kamala Harris", "Donald Trump", "Kamala Harris", "Kamala Harris", 
    "Donald Trump", "Kamala Harris", "Kamala Harris", "Kamala Harris", 
    "Donald Trump", "Donald Trump", "Donald Trump", "Kamala Harris", 
    "DID NOT VOTE IN 2024", "Kamala Harris", "Donald Trump", 
    "Donald Trump", "Donald Trump", "Kamala Harris", "DID NOT VOTE IN 2024", 
    "DID NOT VOTE IN 2024", "Kamala Harris", "Donald Trump", 
    "Kamala Harris", "Kamala Harris", "Donald Trump", "Donald Trump", 
    "Kamala Harris", "Kamala Harris", NA, "Kamala Harris", "Kamala Harris", 
    "Kamala Harris", "Kamala Harris", "DID NOT VOTE IN 2024", 
    "DID NOT VOTE IN 2024", "Kamala Harris", "Kamala Harris", 
    "Donald Trump", "Donald Trump", "Donald Trump", "Donald Trump", 
    "Kamala Harris"), RACIALIDENTITY.6 = c("Black", "White", 
    "Mixed", "Asian", "White", "Black", "White", "White", "White", 
    "White", "White", "Other", "Black", "Mixed", "Other", "Black", 
    "Black", "White", "Black", "White", "White", "Black", "Black", 
    "Asian", "White", "Black", "Latine", "White", "White", "Asian", 
    "Black", "Asian", "Latine", "Mixed", "Asian", "Asian", "Mixed", 
    "Latine", "White", "Latine", "White", "White", "Latine", 
    "White", "Latine", "Asian", "Asian", "White", "Black", "White", 
    "Mixed", "White", "Black", "Black", "Black", "White", "White", 
    "Black", "Latine", "Asian", "Black", "White", "White", "Black", 
    "Black", "White", "Black", "White", "White", "White", "White", 
    "Other", "White", "Black", "Asian", "White", "White", "White", 
    "White", "Asian", "Mixed", "White", "Latine", "Black", "Asian", 
    "Black", "Mixed", "White", "Black", "Black", "White", "Black", 
    "White", "White", "Black", "Asian", "Latine", "Asian", "Asian", 
    "Asian", "White", "Mixed", "White", "Mixed", "Asian", "White", 
    "White", "Asian", "Black", "White", "White", "White", "Asian", 
    "Asian", "White", "Asian", "Asian", "White", "Asian", "Mixed", 
    "Black", "White"), RACIALIDENTITY.4 = c("Black", "White", 
    "Mixed/Other", "Asian", "White", "Black", "White", "White", 
    "White", "White", "White", "Mixed/Other", "Black", "Mixed/Other", 
    "Mixed/Other", "Black", "Black", "White", "Black", "White", 
    "White", "Black", "Black", "Asian", "White", "Black", "Mixed/Other", 
    "White", "White", "Asian", "Black", "Asian", "Mixed/Other", 
    "Mixed/Other", "Asian", "Asian", "Mixed/Other", "Mixed/Other", 
    "White", "Mixed/Other", "White", "White", "Mixed/Other", 
    "White", "Mixed/Other", "Asian", "Asian", "White", "Black", 
    "White", "Mixed/Other", "White", "Black", "Black", "Black", 
    "White", "White", "Black", "Mixed/Other", "Asian", "Black", 
    "White", "White", "Black", "Black", "White", "Black", "White", 
    "White", "White", "White", "Mixed/Other", "White", "Black", 
    "Asian", "White", "White", "White", "White", "Asian", "Mixed/Other", 
    "White", "Mixed/Other", "Black", "Asian", "Black", "Mixed/Other", 
    "White", "Black", "Black", "White", "Black", "White", "White", 
    "Black", "Asian", "Mixed/Other", "Asian", "Asian", "Asian", 
    "White", "Mixed/Other", "White", "Mixed/Other", "Asian", 
    "White", "White", "Asian", "Black", "White", "White", "White", 
    "Asian", "Asian", "White", "Asian", "Asian", "White", "Asian", 
    "Mixed/Other", "Black", "White"), RACIALIDENTITY.2 = c("Else", 
    "White", "Else", "Else", "White", "Else", "White", "White", 
    "White", "White", "White", "Else", "Else", "Else", "Else", 
    "Else", "Else", "White", "Else", "White", "White", "Else", 
    "Else", "Else", "White", "Else", "Else", "White", "White", 
    "Else", "Else", "Else", "Else", "Else", "Else", "Else", "Else", 
    "Else", "White", "Else", "White", "White", "Else", "White", 
    "Else", "Else", "Else", "White", "Else", "White", "Else", 
    "White", "Else", "Else", "Else", "White", "White", "Else", 
    "Else", "Else", "Else", "White", "White", "Else", "Else", 
    "White", "Else", "White", "White", "White", "White", "Else", 
    "White", "Else", "Else", "White", "White", "White", "White", 
    "Else", "Else", "White", "Else", "Else", "Else", "Else", 
    "Else", "White", "Else", "Else", "White", "Else", "White", 
    "White", "Else", "Else", "Else", "Else", "Else", "Else", 
    "White", "Else", "White", "Else", "Else", "White", "White", 
    "Else", "Else", "White", "White", "White", "Else", "Else", 
    "White", "Else", "Else", "White", "Else", "Else", "Else", 
    "White"), RI_White = c(0L, 1L, 0L, 0L, 1L, 0L, 1L, 1L, 1L, 
    1L, 1L, 0L, 0L, 0L, 0L, 0L, 0L, 1L, 0L, 1L, 1L, 0L, 0L, 0L, 
    1L, 0L, 0L, 1L, 1L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 1L, 
    0L, 1L, 1L, 0L, 1L, 0L, 0L, 0L, 1L, 0L, 1L, 0L, 1L, 0L, 0L, 
    0L, 1L, 1L, 0L, 0L, 0L, 0L, 1L, 1L, 0L, 0L, 1L, 0L, 1L, 1L, 
    1L, 1L, 0L, 1L, 0L, 0L, 1L, 1L, 1L, 1L, 0L, 0L, 1L, 0L, 0L, 
    0L, 0L, 0L, 1L, 0L, 0L, 1L, 0L, 1L, 1L, 0L, 0L, 0L, 0L, 0L, 
    0L, 1L, 0L, 1L, 0L, 0L, 1L, 1L, 0L, 0L, 1L, 1L, 1L, 0L, 0L, 
    1L, 0L, 0L, 1L, 0L, 0L, 0L, 1L), RI_Else = c(1L, 0L, 1L, 
    1L, 0L, 1L, 0L, 0L, 0L, 0L, 0L, 1L, 1L, 1L, 1L, 1L, 1L, 0L, 
    1L, 0L, 0L, 1L, 1L, 1L, 0L, 1L, 1L, 0L, 0L, 1L, 1L, 1L, 1L, 
    1L, 1L, 1L, 1L, 1L, 0L, 1L, 0L, 0L, 1L, 0L, 1L, 1L, 1L, 0L, 
    1L, 0L, 1L, 0L, 1L, 1L, 1L, 0L, 0L, 1L, 1L, 1L, 1L, 0L, 0L, 
    1L, 1L, 0L, 1L, 0L, 0L, 0L, 0L, 1L, 0L, 1L, 1L, 0L, 0L, 0L, 
    0L, 1L, 1L, 0L, 1L, 1L, 1L, 1L, 1L, 0L, 1L, 1L, 0L, 1L, 0L, 
    0L, 1L, 1L, 1L, 1L, 1L, 1L, 0L, 1L, 0L, 1L, 1L, 0L, 0L, 1L, 
    1L, 0L, 0L, 0L, 1L, 1L, 0L, 1L, 1L, 0L, 1L, 1L, 1L, 0L), 
    GENDER_MALE = c(1L, 1L, 1L, 0L, 1L, 0L, 0L, 1L, 0L, 0L, 1L, 
    0L, 0L, 0L, 1L, 0L, 0L, 1L, 0L, 1L, 0L, 1L, 1L, 1L, 0L, 0L, 
    0L, 0L, 0L, 1L, 0L, 1L, 0L, 0L, 1L, 0L, 1L, 1L, 1L, 1L, 1L, 
    1L, 0L, 1L, 1L, 0L, 0L, 1L, 1L, 0L, 1L, 1L, 1L, 0L, 0L, 1L, 
    0L, 0L, 1L, 0L, 1L, 0L, 0L, 1L, 1L, 0L, 0L, 0L, 1L, 0L, 0L, 
    1L, 1L, 1L, 0L, 1L, 0L, 0L, 1L, 1L, 1L, 1L, 1L, 0L, 0L, 0L, 
    1L, 1L, 1L, 1L, 0L, 0L, 0L, 0L, 1L, 1L, 0L, 1L, 1L, 0L, 0L, 
    1L, 1L, 0L, 0L, 0L, 0L, 1L, 1L, 1L, 1L, 1L, 0L, 0L, 1L, 0L, 
    1L, 1L, 1L, 0L, 1L, 0L), RACE_BLACK = c(1L, 0L, 0L, 0L, 0L, 
    1L, 0L, 0L, 0L, 0L, 0L, 0L, 1L, 0L, 0L, 1L, 1L, 0L, 1L, 0L, 
    0L, 1L, 1L, 0L, 0L, 1L, 0L, 0L, 0L, 0L, 1L, 0L, 0L, 0L, 0L, 
    0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 1L, 0L, 
    0L, 0L, 1L, 1L, 1L, 0L, 0L, 1L, 0L, 0L, 1L, 0L, 0L, 1L, 1L, 
    0L, 1L, 0L, 0L, 0L, 0L, 0L, 0L, 1L, 0L, 0L, 0L, 0L, 0L, 0L, 
    0L, 0L, 0L, 1L, 0L, 1L, 0L, 0L, 1L, 1L, 0L, 1L, 0L, 0L, 1L, 
    0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 1L, 0L, 
    0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 1L, 0L), RACE_ASIAN = c(0L, 
    0L, 0L, 1L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 
    0L, 0L, 0L, 0L, 0L, 0L, 0L, 1L, 0L, 0L, 0L, 0L, 0L, 1L, 0L, 
    1L, 0L, 0L, 1L, 1L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 1L, 
    1L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 1L, 0L, 
    0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 1L, 0L, 
    0L, 0L, 0L, 1L, 0L, 0L, 0L, 0L, 1L, 0L, 0L, 0L, 0L, 0L, 0L, 
    0L, 0L, 0L, 0L, 1L, 0L, 1L, 1L, 1L, 0L, 0L, 0L, 0L, 1L, 0L, 
    0L, 1L, 0L, 0L, 0L, 0L, 1L, 1L, 0L, 1L, 1L, 0L, 1L, 0L, 0L, 
    0L), RACE_OTHER = c(0L, 0L, 1L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 
    0L, 1L, 0L, 1L, 1L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 
    0L, 1L, 0L, 0L, 0L, 0L, 0L, 1L, 1L, 0L, 0L, 1L, 1L, 0L, 1L, 
    0L, 0L, 1L, 0L, 1L, 0L, 0L, 0L, 0L, 0L, 1L, 0L, 0L, 0L, 0L, 
    0L, 0L, 0L, 1L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 
    0L, 1L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 1L, 0L, 1L, 0L, 0L, 
    0L, 1L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 1L, 0L, 0L, 0L, 
    0L, 1L, 0L, 1L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 
    0L, 0L, 0L, 0L, 1L, 0L, 0L), RELIGIOUS_YES = c(1L, 0L, 0L, 
    1L, 1L, 1L, 1L, 0L, 1L, 1L, 1L, 1L, 1L, 0L, 1L, 1L, 1L, 1L, 
    1L, 1L, 1L, 1L, 1L, 1L, 1L, 0L, 1L, 1L, 1L, 0L, 1L, 1L, 1L, 
    0L, 0L, 0L, 0L, 0L, 0L, 1L, 1L, 0L, 1L, 0L, 1L, 1L, 0L, 1L, 
    0L, 0L, 0L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 0L, 0L, 1L, 1L, 0L, 
    1L, 1L, 0L, 1L, 1L, 0L, 1L, 1L, 0L, 1L, 0L, 0L, 0L, 1L, 1L, 
    1L, 1L, 1L, 0L, 0L, 0L, 1L, 1L, 0L, 1L, 1L, 1L, 1L, 1L, 0L, 
    1L, 1L, 0L, 1L, 0L, 1L, 1L, 0L, 1L, 1L, 0L, 1L, 1L, 0L, 1L, 
    1L, 0L, 0L, 1L, 0L, 0L, 0L, 0L, 0L, 0L, 1L, 1L, 0L, 1L), 
    EDUCATION_HIGH = c(1L, 0L, 0L, 1L, 1L, 1L, 0L, 1L, 0L, 0L, 
    1L, 1L, 1L, 1L, 1L, 0L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 
    0L, 0L, 1L, 1L, 0L, 1L, 1L, 0L, 0L, 1L, 0L, 0L, 0L, 1L, 1L, 
    1L, 1L, 1L, 0L, 0L, 1L, 1L, 1L, 1L, 1L, 0L, 1L, 0L, 1L, 1L, 
    1L, 1L, 1L, 0L, 1L, 1L, 1L, 0L, 1L, 1L, 0L, 1L, 0L, 1L, 1L, 
    1L, 1L, 1L, 1L, 1L, 1L, 0L, 1L, 1L, 0L, 0L, 1L, 1L, 0L, 1L, 
    1L, 1L, 1L, 1L, 1L, 1L, 0L, 0L, 1L, 1L, 1L, 1L, 1L, 0L, 0L, 
    1L, 1L, 1L, 0L, 1L, 1L, 0L, 1L, 1L, 1L, 1L, 0L, 1L, 1L, 0L, 
    1L, 1L, 0L, 0L, 1L, 1L, 1L)), row.names = c(NA, 122L), class = "data.frame")

15.2 Example Dataset

The example dataset is a small subset of a larger dataset collected via Prolific on March, 15, 2025. For more information, review the read me file.

15.3 Inline R Code

The traditional process of writing a results section of a research paper usually involves three steps: 1) running the analyses, 2) copying statistics and p-values from the data analysis software into a word document, and 3) writing text to interpret the results. In each of these steps, researchers can make an error. Using inline R code eliminates step2 of copying-and-pasting of numbers into a report or manuscript and reduces parts of step 3. Below are a few examples of how to use inline R code to generate numbers or text using functions:

Report Sample Size
Report Numbers and Percentages
Write Numbers as Words
Report Descriptive Stats in a Table
Report a Parameter and p-value

15.4 Example 1: Report Sample Size

15.4.1 create object: `total_responses`

15.5 use in line code

In your manuscript, write like this:

We surveyed a total of `r total_responses` participants.

When you render the output, you’ll get:

We surveyed a total of 122 participants.

15.6 Example 2: Report Numbers and Percentages

You can combine counts and percentages easily.

15.6.1 create an object for the sum of each racial identity in the sample

15.6.2 use inline r code with `total_responses`

In your manuscript, write like this:

Out of `r total_responses` participants, The final sample was roughly balanced in terms of 
racial identity (White: `r percent(white, accuracy = 0.1)`, 
                 Black: `r percent(black, accuracy = 0.1)`,
                 Asian: `r percent(asian, accuracy = 0.1)`, 
                 Mixed/Other: `r percent(mixed_other, accuracy = 0.1)`).

When you render the output, you’ll get:

Out of 122 participants, The final sample was roughly balanced in terms of racial identity
(White: 40.2%, Black: 23.0%, Asian: 18.9%, Mixed/Other: 18.0%).

15.7 Example 3: Write Numbers as Words

15.7.1 load library

15.7.2 report numbers as words

In your manuscript, write like this:

A total of `r str_to_title(as.character(english(total_responses)))` participants were included in the analysis.

When you render the output, you’ll get:

A total of One Hundred And Twenty-Two participants were included in the analysis.

15.8 Example 4: Report descriptive statistics in a table a table by using inline R code (Mean, SD, Range)

Writing functions can help researchers output the mean, median, sd, min, max and output these descriptive statistics into a table.

15.8.1 create variables

# Define Continuous Variables
continuous_vars <- c("AGE", "SOCIALSTATUS", "POLITICALBELIEFS", paste0("ZEROSUM_", 1:11)
)

desc_table_continuous <- select_data %>%
  select(all_of(continuous_vars)) %>%
  psych::describe() %>%
  tibble::rownames_to_column(var = "Variable") %>% 
  select(Variable, n, mean, median, sd, min, max)

# Create table
knitr::kable(desc_table_continuous, digits = 2)

Descriptive Stats Table for Continuous Variables
Variable	n	mean	median	sd	min	max
AGE	121	36.10	33.0	12.73	19	73
SOCIALSTATUS	122	5.30	5.5	1.78	1	9
POLITICALBELIEFS	120	3.67	4.0	1.35	1	6
ZEROSUM_1	122	3.92	4.0	1.78	1	7
ZEROSUM_2	121	4.75	5.0	1.59	1	7
ZEROSUM_3	121	4.92	5.0	1.49	1	7
ZEROSUM_4	121	3.07	3.0	1.69	1	7
ZEROSUM_5	122	2.84	3.0	1.75	1	7
ZEROSUM_6	121	3.43	3.0	2.07	1	7
ZEROSUM_7	120	3.52	4.0	1.81	1	7
ZEROSUM_8	121	2.93	3.0	1.63	1	7
ZEROSUM_9	121	2.59	2.0	1.74	1	7
ZEROSUM_10	122	3.20	3.0	1.75	1	7
ZEROSUM_11	121	3.17	3.0	1.74	1	7

15.8.2 create table

In your manuscript, write like this:

Descriptive statistics for all study variables are presented in Continuous Descriptive Statistics Table. 
The sample consisted of `r nrow(select_data)` participants, 
with a mean age of `r round(desc_table_continuous$mean[desc_table_continuous$Variable == "AGE"], 2)` 
years (SD = `r round(desc_table_continuous$sd[desc_table_continuous$Variable == "AGE"], 2)`, 
range = `r desc_table_continuous$min[desc_table_continuous$Variable == "AGE"]`
– `r desc_table_continuous$max[desc_table_continuous$Variable == "AGE"]`). 

Participants reported a mean social status of 
`r round(desc_table_continuous$mean[desc_table_continuous$Variable == "SOCIALSTATUS"], 2)` 
(SD = `r round(desc_table_continuous$sd[desc_table_continuous$Variable == "SOCIALSTATUS"], 2)`) on a 10-point scale.

When you render the output, you’ll get:

Descriptive statistics for all study variables are presented in Continuous Descriptive Statistics Table. 
The sample consisted of 122 participants, with a mean age of 36.1 years (SD = 12.73, range = 19 – 73). 
Participants reported a mean social status of 5.3 (SD = 1.78) on a 10-point scale.

15.9 Example 5: Report a parameter and p-values

Inline R code is used to report the parameter and p-value of a Kruskal-Wallis Test.

15.9.1 run analyses

15.9.2 include inline R code with reporting

In your manuscript, write like this:

There was no significant difference in ZEROSUM_1 scores across political party groups, 
Kruskal-Wallis χ²(`r kw.ZEROSUM_1.party$parameter`) = `r round(kw.ZEROSUM_1.party$statistic, 2)`, 
*p* = `r signif(kw.ZEROSUM_1.party$p.value, 3)`.

When you render the output, you’ll get:

There was no significant difference in ZEROSUM_1 scores across political party groups, 
Kruskal-Wallis χ²(2) = 1.5, p = 0.473.

15.10 Common Pitfalls to Avoid

⚠️ Danger: Common Mistakes

Object not found errors - Make sure you create objects, such as total_responses, before using functions, such as percent(), before referencing them inline
Wrong variable names - R is case-sensitive: age ≠ AGE
Missing packages - Load scales and english if outputting english text

15.1 Load Library

15.2 Example Dataset

15.3 Inline R Code

15.4 Example 1: Report Sample Size

15.4.1 create object: total_responses

15.5 use in line code

15.6 Example 2: Report Numbers and Percentages

15.6.1 create an object for the sum of each racial identity in the sample

15.6.2 use inline r code with total_responses

15.7 Example 3: Write Numbers as Words

15.7.1 load library

15.7.2 report numbers as words

15.8 Example 4: Report descriptive statistics in a table a table by using inline R code (Mean, SD, Range)

15.8.1 create variables

15.8.2 create table

15.9 Example 5: Report a parameter and p-values

15.9.1 run analyses

15.9.2 include inline R code with reporting

15.10 Common Pitfalls to Avoid

15.4.1 create object: `total_responses`

15.6.2 use inline r code with `total_responses`