Supplemental Lesson: Creating Table 1, Table 2, and Code Chunks

Alternative Method for gtsummary()

Overview

This lesson shows you how to:

• Create Table 1 (descriptive statistics)
• Create Table 2 (regression results)
• Use Quarto chunk options to control code and output
• Write cleaner, more impactful reports

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Setup

# install.packages(c("dplyr", "knitr", "broom"))
library(dplyr)

Warning: package 'dplyr' was built under R version 4.5.1

Attaching package: 'dplyr'

The following objects are masked from 'package:stats':

    filter, lag

The following objects are masked from 'package:base':

    intersect, setdiff, setequal, union

library(knitr)
library(broom)

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Example Dataset

data(starwars)

df <- starwars %>%
  select(sex, height, mass) %>%
  filter(!is.na(sex))

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Table 1: Descriptive Statistics

Simple Summary Table

table1 <- df %>%
  group_by(sex) %>%
  summarise(
    n = n(),
    mean_height = mean(height, na.rm = TRUE),
    mean_mass = mean(mass, na.rm = TRUE)
  )

kable(table1, caption = "Table 1. Descriptive Statistics by Sex")

Table 1. Descriptive Statistics by Sex

sex	n	mean_height	mean_mass
female	16	171.5714	54.68889
hermaphroditic	1	175.0000	1358.00000
male	60	179.1228	80.21905
none	6	131.2000	69.75000

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Table 2: Regression Results

model <- lm(mass ~ height, data = df)

table2 <- tidy(model)

kable(table2, digits = 3, caption = "Table 2. Linear Regression Results")

Table 2. Linear Regression Results

term	estimate	std.error	statistic	p.value
(Intercept)	-11.248	114.345	-0.098	0.922
height	0.629	0.643	0.977	0.333

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Quarto Tips: Controlling Code & Output

REMEMBER - The code goes INSIDE of the {r}. Make sure to use a comma after each new command.

1. Hide Code, Show Output

   Min. 1st Qu.  Median    Mean 3rd Qu.    Max.    NA's 
   66.0   167.0   180.0   174.6   191.0   264.0       6 

The code: echo=FALSE

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2. Show Code, Hide Output

summary(df$height)

The code: results='hide'

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3. Hide Both Code and Output

The code: include=FALSE

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4. Clean Tables (No Messages or Warnings)

kable(head(df), caption = "Clean Table Example")

Clean Table Example

sex	height	mass
male	172	77
none	167	75
none	96	32
male	202	136
female	150	49
male	178	120

The code: message=FALSE, warning=FALSE

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Writing Tips for Quarto Reports

• Keep text short and clear
• Always interpret your results
• Use table captions to explain what the reader is seeing
• Avoid dumping raw output — format it into tables
• Use headings to organize your report

Example Interpretation

The results suggest that height is positively associated with mass, indicating that taller individuals tend to have higher body mass on average.

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Key Takeaways

• Use kable() for clean, simple tables
• Always structure Table 1 (descriptive) and Table 2 (model results)
• Control what your audience sees using chunk options
• Focus on interpretation, not just output