Introduction - Markdown

Markdown is one of the markup languages along with HTML, XML and TeX. A markup language is deemed as a syntax for annotating a document where formatting is distinguishable from the textual content. That can be done by tags, that can be named elements (<b>bold</b>) or by ASCII punctuation marks and other non-letter symbols.

Markdown is defined as a text-to-HTML conversion tool based on the formatting syntax and the software tool to convert text to HTML. It was created in 2004 by John Gruber and Aaron Swartz and is classified a lightweight markup language. Its main advantage is having a comprehensive syntax, meaning that the plain text document is easily understandable, facilitating reading and writing.

# Heading with markdown
## Heading 2 with markdown

<h1>Header with HTML</h1> 
<h2>Heading 2 with HTML</h2>

It can be used to create different types of documents: books, presentations, websites, technical documentation and can be mixed with some other applications on R. Markdown is used in GitHub and Bitbucket software tutorials and Reddit posts. In fact, this training was organized on Markdown, combined with R, HTML and CSS. Markdown can also directly “understand” other languages as HTML, CSS and LaTeX. Due to this support, you can use HTML code directly on Markdown and it will be properly formatted.

The common filename extensions for Markdown documents are .md and .markdown. For R Markdown plain-text file the extension used is .Rmd. Jupyter notebooks text cells use Markdown.

Installation - R Markdown

R Markdown documents can be created directly on R (R Core team), you will just need to install Pandoc, that is a document converter - essential for mixing different types of markup languages in the same document. If you use RStudio, Pandoc comes with the IDE.

The next step is to install the rmarkdown package:

# From CRAN
install.packages("rmarkdown")

For generating pdf documents, you will also need to install LaTeX and its dependencies in your computer. There second option is to install TinyTex (Xie 2021) - a portable and lightweight LaTeX distribution, that can be installed in multiple platforms:

install.packages('tinytex')
tinytex::install_tinytex()  # install TinyTeX

First R Markdown document

On the upper left corner, click in the New File button and select R Markdown (File -> New File -> R Markdown). Then choose a title for your document, include your name as author and select PDF as output format:

As you noticed, RStudio created a template document for you. Before we move forward, please save your file in the folder of your preference.

The beginning of the .Rmd contains metadata of the document between three dashes. It is formatted in YAML instead of Markdown. Do not worry about that, is just a data-serialization language that is important for the configuration files. It looks like:

---
title: "Research Design - R Markdown training"
author: "Author"
date: "11/29/2021"
output: pdf_document
---

See that it has the metadata of the file (title, author and date) as well as the output information (PDF format). Other information can be added, especially in the output part.

Please delete anything below the metadata in your Rmd document! We are going to build it together.

---
title: "Research Design - R Markdown training"
author: "Author"
date: "11/16/2021"
output: pdf_document
---

This is my first R Markdown document.

Basic syntax

The syntax used in R Markdown is the Pandoc’s Markdown. Here we will describe the most common syntax elements for beginners.

*italics* or _italics_
**bold** or __bold__

C~6~H~12~O~6~ + 6O~2~ --> 6CO~2~ + 6H~2~O

Fe^2+^ --> Fe^3+^ + e^-^

Here is the link to access the [Montana State University](https://www.montana.edu) website.

![](./MSU-vert.png)

![](https://www.montana.edu/creativeservices/images/MSU-vert.png)

Write an inline `code`

# Header - Level 1

## Header - Level 2

### Header - Level 3

#### Header - Level 4

* Item 1
* Item 2
* Item 3

* ANOVA
* Designs
   * Completely Randomized Design
   * Randomized Block Design

1. Hey

2. Enumerated

3. List

   * unordered list

- [ ] unchecked task 
- [x] checked task

$y_{ij} = \beta_{0} + \beta_{i} + \gamma_{j} + (\beta\gamma)_{ij}$

$\begin{bmatrix} y_{11} \\
y_{12} \\
y_{21} \\
y_{22}
\end{bmatrix} = 
\begin{bmatrix} 1 & x_{11} \\
1 & x_{12} \\
1 & x_{21} \\
1 & x_{22}
\end{bmatrix}$

R code chunks

Now it is time to put together everything you have been learning about Research Design and R! To create a code chunk, just click on the Insert a new code chunk or by the shortcut (Ctrl + Alt + I or Cmd + Option + I):

```{r}


```

Inside the chunk we can write our R code, as we do in a script. To print the simple Hello World, we just include it in the chunk:

```{r}
cat("Hello World")
```

## Hello World

Now, let’s use the content from Unplanned Comparisons to illustrate how to include an analysis inside R Markdown.

```{r}
# This script illustrates the use of means separations tests
# read in and inspect the data
# Make data frame
weight <- c(4.23, 4.38, 4.10, 3.99, 4.25,
            3.85, 3.78, 3.91, 3.94, 3.86,
            3.75, 3.65, 3.82, 3.69, 3.73,
            3.66, 3.67, 3.62, 3.54, 3.71)
acid <- c(rep("Control", 5),
          rep("HCl", 5), 
          rep("Propionic", 5),
          rep("Butyric", 5))

d <- data.frame(acid, weight)
d$acid <- as.factor(d$acid)
str(d)
```

If we knit the document, we will get the following output:

## 'data.frame':    20 obs. of  2 variables:
##  $ acid  : Factor w/ 4 levels "Butyric","Control",..: 2 2 2 2 2 3 3 3 3 3 ...
##  $ weight: num  4.23 4.38 4.1 3.99 4.25 3.85 3.78 3.91 3.94 3.86 ...

This is not limited to text output. Plots can be directly shown on document:

```{r}
boxplot(weight ~ acid, data = d)
```

Now you can organize your results from ANOVA and any other tests in a single report. We can also make things fancier. First, let’s create an ANOVA table based on the linear model:

```{r}
mod1<-lm(weight ~ acid, data = d)
anova(mod1)
```

## Analysis of Variance Table
## 
## Response: weight
##           Df  Sum Sq  Mean Sq F value    Pr(>F)    
## acid       3 0.87369 0.291232  33.874 3.669e-07 ***
## Residuals 16 0.13756 0.008597                      
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1

We can then use the function kable from package knitr:

```{r}
mod1<-lm(weight ~ acid, data = d)
knitr::kable(anova(mod1))
```

Controlling the outputs

We can control the outputs of the chunks using arguments inside the curling brackets ```{r OPTION}. Among the options, we can control the width and height of the figure, align the plot, evaluate the chunk and also hide it.

Evaluate the code

```{r eval=FALSE}
cat("I will not be evaluated!")
```

Hide the code

```{r echo=FALSE}
cat("My code is hidden! :) ")
```

Hide the result

```{r result='hide'}
cat("No result is shown here!")
```

Warnings, messages and errors

We can also hide messages provided by the packages, as well as warnings and errors. We simply use warning=FALSE.

```{r warning=FALSE}
warning("This is a warning")
```

Figure parameters

Width, heigth and alignment:

```{r fig.width=5, fig.height=3, fig.align='center'}
boxplot(weight ~ acid, data = d)
```

Figure caption:

```{r fig.width=5, fig.height=3, fig.cap="Figure 1 - This is our first figure."}
boxplot(weight ~ acid, data = d)
```

Figure 1 - This is our first figure.

Other languages

The package knitr offers support to a large number of language engines. It allow us to create documents using other programming languages (combined in the same document or not).

Bash

```{bash}
echo "Hello world"
```

## Hello world

Python

```{python, python.reticulate=FALSE}
x = 'hello world!'
print(x)
print(x.split(" "))
```

## hello world!
## ['hello', 'world!']

Questions ?

References

Xie, Y.; Allaire, J.J.; Grolemund, G. R Markdown: The Definitive Guide

Daring Fireball - by John Gruber. Markdown

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