All flavors markdown

Pablo Mosteiro
p.mosteiro@uu.nl

Methodology & Statistics @ UU

Hanne Oberman
h.i.oberman@uu.nl

Methodology & Statistics @ UU

23 Sep 2026

Disclaimer

These materials are generated by Gerko Vink, who used to coordinate this course and holds the copyright. Gerko owes a debt of gratitude to many people as the thoughts and code in these slides are the process of years-long development cycles and discussions with his team, friends, colleagues and peers. When someone has contributed to the content of the slides, he has credited their authorship.

The intellectual property belongs to Utrecht University. Images are either directly linked, or generated with StableDiffusion or DALL-E. That said, there is no information in this presentation that exceeds legal use of copyright materials in academic settings, or that should not be part of the public domain.

Warning

You may use any and all content in this presentation - excluding names - and submit it as input to generative AI tools, with the following exception:

  • You must ensure that the content is not used for further training of the model

Open Source:

Today’s lecture

  • Markdown basics
  • Reference management
  • Quarto for academic writing and presenting

Take aways

  • Quarto markdown is tool to integrate text, figures, code and output
  • Quarto enables data scientists/statisticians to communicate productively and reproducibly
  • There is a universe of plugins and add-ons to make your academic life easier

Markdown basics

What is Markdown?

  • Markdown is a lightweight markup language for creating formatted text using plain text. It’s easy to learn and widely used in various applications.

  • Markdown is not WYSIWYG.

  • Instead, plain text with markup instructions are converted to marked up text (e.g., *italics* becomes italics).

Source: Markdown Guide

Some Markdown flavors

  • GitHub-Flavored Markdown (GFM) is a variant of Markdown used on GitHub (next week), enhancing its capabilities for documentation and collaboration.

  • Jupyter Notebooks: Widely used interactive kernel-based computing environment for data science and machine learning, supporting multiple (i.e. almost all) programming and scripting languages.

  • RMarkdown: An R-based notebook environment that allows you to embed R code and its output directly within a document; combining code, output, and narrative text in a single document.

  • Quarto: Next generation markdown for R, Python, Julia, etc. Perfect for creating reproducible reports, research papers, and presentations.

Using Markdown in an IDE

Popular IDEs for R:

  • RStudio: Ideal for R programming with features tailored for data analysis and visualization.
  • Positron/Visual Studio Code (VS Code): A versatile code editor with a vast ecosystem of extensions for various languages.
  • Eclipse (with StatET): Eclipse StatET is an integrated development environment (IDE) for R, offering features for R programming and data analysis.

RStudio

Structure of a Quarto Document

  • A Quarto document is organized into blocks, which serve as the fundamental building blocks of the document’s content.
  • Each block can contain a combination of the following elements:
    • YAML Headers: Metadata and document configuration.
    • Sections and Subsections: Structuring the document into hierarchical sections for organization.
    • Text: Narrative content and explanations.
    • Equations: Mathematical equations and notation.
    • Figures: Visualizations, charts, and images.
    • Tables: Data tables for presenting results.
    • Code: R code chunks for computations and data analysis.

The YAML header

YAML (YAML Ain’t Markup Language) is a human-readable data serialization format commonly used for configuration files and metadata in various programming and markup contexts.

---
title: "A minimum example of YAML code"
---

  • YAML is very simple and readable

  • In Quarto and many other applications, YAML is used to specify:

    • Document Metadata: Information about the document itself, such as the title, author, date, and document type.

    • Document Configuration: Settings related to the document’s behavior, appearance, and rendering, such as the output format (e.g., HTML, PDF), document template, and style options.

    • Custom Variables: Definitions of custom variables or parameters that can be used throughout the document to control behavior or content.

The YAML header of a Quarto document

The YAML header is a powerful tool for customizing and configuring Quarto documents, allowing you to control how the document is rendered and presented. It ensures that important document information and settings are stored in a human-readable and structured format at the beginning of the document.

  • title, author, and date provide metadata about the document.
  • output specifies settings related to the document’s output format and theme.
---
title: "All flavors markdown"
author: 
  - name: Gerko Vink
    orcid: 0000-0001-9767-1924
    email: g.vink@uu.nl
    affiliations:
      - name: Methodology & Statistics @ UU University
  - name: Hanne Oberman
    orcid: 0000-0003-3276-2141
    email: h.i.oberman@uu.nl
    affiliations:
      - name: Methodology & Statistics @ UU
date: 25 Sep 2024
date-format: "D MMM YYYY"
bibliography: data/lec-2/publications.bib
execute: 
  echo: true
editor: source
format: 
  revealjs:
    embed-resources: true
    theme: [solarized, gerko.scss]
    progress: true
    multiplex: true
    transition: fade
    slide-number: true
    margin: 0.075
    logo: "images/logo.png" 
    toc: false
    toc-depth: 1
    toc-title: Outline
    scrollable: true
    reference-location: margin
    footer: Gerko Vink and Hanne Oberman - Markup Languages @ UU
---

Text and headers

  • Text is text. Nothing more, nothing less.

  • Headers are generated using #s

# This is a heading indicating a section
## This is a heading indicating a subsection
### This is a heading indicating a subsubsection

How would you generate these headers?

Subheader

Subsubheader


### Header
#### Subheader
##### Subsubheader

Why?

A single # denotes a section in slides

A double ## denotes a slide

It is that simple. No more framing in \(\LaTeX\) or other stuff. Just use the # and ## to denote a section and a slide.

Equations

  • $\mu$ is used for in-line equations
  • $$\mu$$ is used for equations

Plain text:

Let's assume that $Y$ follows a normal distribution. 

$$Y \sim  \mathcal{N}(\mu, \sigma^2)$$ 

Where we set in our simulations $\mu = 10$ and $\sigma^2 = 5$. We do something for every $Y_i$.

Marked up text:

Let’s assume that \(Y\) follows a normal distribution. \[Y \sim \mathcal{N}(\mu, \sigma^2)\] Where we set in our simulations \(\mu = 10\) and \(\sigma^2 = 5\). We do something for every \(Y_i\).

Equations

Plain text:

Let's assume that $y$ is a vector with $n$ elements such that

$$y \sim  \mathcal{N}(\mu, \sigma^2),$$ 

where we set in our simulations $\mu = 10$ and $\sigma^2 = 5$. 

We do something for every $y_i$ with $i = 1, \dots, n$.

Marked up text:

Let’s assume that \(y\) is a vector with \(n\) elements such that \[y \sim \mathcal{N}(\mu, \sigma^2),\] where we set in our simulations \(\mu = 10\) and \(\sigma^2 = 5\). We do something for every \(y_i\) with \(i = 1, \dots, n\).

Images

Plain text:

Add an image from the internet 
![](https://quarto.org/docs/
  authoring/elephant-dark.png)

Marked up text:

Add an image from the internet

Images

Plain text:

Add an image from your PC
![](images/lec-2/elephantastic.png)

Marked up text:

Add an image from your PC

Images

Plain text:

Generate an image with code

```{r}

plot(1:10)

```

Marked up text:

Generate an image with code

plot(1:10)

Images

Plain text:

Generate an image with code

```{r}

#| echo: false

plot(1:10)

```

Marked up text:

Generate an image with code

Diagrams

```{{mermaid}}
%%| echo: fenced
flowchart LR
  A[Hard edge] --> B(Round edge)
  B --> C{Decision}
  C <--> D[Result one]
  C --> E[Result two]
```


flowchart LR
  A[Hard edge] --> B(Round edge)
  B --> C{Decision}
  C <--> D[Result one]
  C --> E[Result two]

See Quarto Diagrams for a more comprehensive overview of all graphing engines. This Live online Mermaid editor is awesome!

Interactive figures

library(dygraphs)
dygraph(nhtemp, main = "New Haven Temperatures", ylab = "Temp (F)")

Interactive figures

library(dygraphs)
dygraph(nhtemp, main = "New Haven Temperatures", ylab = "Temp (F)")

Interactive figures

library(ggplot2, warn.conflicts = FALSE)
library(plotly, warn.conflicts = FALSE)
ggplot(mpg, aes(displ, hwy, colour = class)) +
  geom_point() +
  geom_smooth(se = FALSE, method = lm)

Interactive figures

library(ggplot2, warn.conflicts = FALSE)
library(plotly, warn.conflicts = FALSE)
p <- ggplot(mpg, aes(displ, hwy, colour = class)) +
  geom_point() +
  geom_smooth(se = FALSE, method = lm) 
ggplotly(p)

Tables

Use tibbles (or gt) for static tables:

mice::boys |> 
  tibble::as_tibble()
# A tibble: 748 × 9
     age   hgt   wgt   bmi    hc gen   phb      tv reg  
   <dbl> <dbl> <dbl> <dbl> <dbl> <ord> <ord> <int> <fct>
 1 0.035  50.1  3.65  14.5  33.7 <NA>  <NA>     NA south
 2 0.038  53.5  3.37  11.8  35   <NA>  <NA>     NA south
 3 0.057  50    3.14  12.6  35.2 <NA>  <NA>     NA south
 4 0.06   54.5  4.27  14.4  36.7 <NA>  <NA>     NA south
 5 0.062  57.5  5.03  15.2  37.3 <NA>  <NA>     NA south
 6 0.068  55.5  4.66  15.1  37   <NA>  <NA>     NA south
 7 0.068  52.5  3.81  13.8  34.9 <NA>  <NA>     NA south
 8 0.071  53    3.89  13.8  35.8 <NA>  <NA>     NA west 
 9 0.071  55.1  3.88  12.8  36.8 <NA>  <NA>     NA west 
10 0.073  54.5  4.2   14.1  38   <NA>  <NA>     NA east 
# ℹ 738 more rows

Or use https://www.tablesgenerator.com/markdown_tables if you want to manually edit a static table.

Tables

Use library(DT) for interactive tables and customization:

library(DT)
mtcars |> 
  datatable(options = list(pageLength = 25))

Cross-referencing

Plain text:

```{r}

#| label: fig-one
#| fig-cap: Nonsense graph
#| echo: false

plot(1:10)

```

Used inline as @fig-one.

Marked up text:

Figure 1: Nonsense graph

Used inline as Figure 1.

Cross-referencing

Plain text:

```{r}

#| label: tbl-penguins
#| tbl-cap: Penguins data
#| echo: false

gtsummary::tbl_summary(penguins)

```

Used inline as @tbl-penguins.

Marked up text:

Table 1: Penguins data
Characteristic N = 3441
species
    Adelie 152 (44%)
    Chinstrap 68 (20%)
    Gentoo 124 (36%)
island
    Biscoe 168 (49%)
    Dream 124 (36%)
    Torgersen 52 (15%)
bill_len 44.5 (39.2, 48.5)
    Unknown 2
bill_dep 17.30 (15.60, 18.70)
    Unknown 2
flipper_len 197 (190, 213)
    Unknown 2
body_mass 4,050 (3,550, 4,750)
    Unknown 2
sex
    female 165 (50%)
    male 168 (50%)
    Unknown 11
year
    2007 110 (32%)
    2008 114 (33%)
    2009 120 (35%)
1 n (%); Median (Q1, Q3)

Used inline as Table 1.

Referencing

Citing literature

Plain text:

Use inline citations @ref.

Marked up text:

Use inline citations (ref?).


References require a bibliography entry, such as in a .bib file:

@book{ref,
  title     = {Name of the book (or article, etc.)},
  author    = {Lastname, Firstname},
  year      = {2026}
}

Bibliography files

  • BibTeX is the classic bibliography system for LaTeX.
  • It stores references in a .bib file, links them by citation keys, and formats output with a selected bibliography style.
  • The .bib file’s role is to store bibliographic records, and only entries that have been cited* will appear in the reference list.

* e.g., via \cite{...} in .tex files, or @... in Quarto

Reference management software

  • What is RMS?
    • Database of bibliographic records
    • Creator of bibliographic citations
    • Document and knowledge management
      • Collection structure
      • Tags
      • Notetaking

Zotero [zoh-TAIR-oh] is a free, easy-to-use tool to help you collect, organize, cite, and share your research sources. - Zotero’s quick start guide

Install & setup Zotero

  1. Go to zotero.org

Create a web account

  1. Go to zotero.org
  2. Click Log In

Create a web account

  1. Go to zotero.org
  2. Click Log In
  3. Click Register for a free account

Create a web account

  1. Go to zotero.org
  2. Click Log In
  3. Click Register for a free account
  4. Fill out the info

Create a web account

  1. Go to zotero.org
  2. Click Log In
  3. Click Register for a free account
  4. Fill out the info
  5. Click Register

Download Zotero for your Operating System

At zotero.org/download

Details

  • Mac
  • Windows
  • Linux
  • Chromebook
  • Automatically updates

Zotero Connector in browser simplifies storing articles

At zotero.org/download

Details

  • Firefox (Recommended)
  • Chrome
  • Edge
  • Safari

Optionally: download the app

  • Benefits
    • Portability
    • interoperability
    • Gathering and managing on the go
      • Share \(\rightarrow\) Zotero app

Click your operating system below:

Google Play Button
Download on the App Store

Downloading plugins to extend Zotero’s abilities

  • Download the .xpi file for the version you want
    • For Firefox, right-click and Save Link As...
      • OR! Set the Boolean for browser.altClickSave to true at about:config

Install plugins to complete Zotero’s extenstion

  1. Open Zotero

Install plugins to complete Zotero’s extenstion

  1. Open Zotero
  2. Select Tools \(\rightarrow\) Plugins

Install plugins to complete Zotero’s extenstion

  1. Open Zotero
  2. Select Tools \(\rightarrow\) Plugins
  3. Select the gear (⚙️) in the top-right corner

Install plugins to complete Zotero’s extenstion

  1. Open Zotero
  2. Select Tools \(\rightarrow\) Plugins
  3. Select the gear (⚙️) in the top-right corner
  4. Choose Install Plugins From File…

Install plugins to complete Zotero’s extenstion

  1. Open Zotero
  2. Select Tools \(\rightarrow\) Plugins
  3. Select the gear (⚙️) in the top-right corner
  4. Choose Install Plugins From File…
  5. Choose .xpi files to install
  6. Select Open
  7. Select Install
  8. Restart Zotero

Plugins

Download and install Zotero plugins (as .xpi files) to get:

Citations

Marked up text:

Oberman and Vink (2023) and Cai, Van Buuren and Vink (2023) are some of our team’s most recent publications. Some references - such as some work by Reinder Banning and Gerko Vink are much older (2010) or contain simple and contemporary solutions by Volker and Vink (2022, 2–4) or cool but potentially confusing images (Schouten and Vink 2021, 1255).


Plain text:

@eval and Cai, Van Buuren and Vink [-@cai2023graphical] are some of our team's most recent publications. Some references - such as some work by Reinder Banning and Gerko Vink are much older [-@banningvink] or contain simple and contemporary solutions by @vigntg [p. 2-4] or cool but potentially confusing images [@schouten2021dance, 1255].

::: footer
But you can also refer to @eval here
:::

But you can also refer to Oberman and Vink (2023) here

Reference list

Marked up text:

Banning, Reinder, and Gerko Vink. 2010. Methoden En Indicatoren Voor Het Evalueren En Beschrijven van Controle- En Correctieprocessen. CBS Nota DMV-2010- 06-08-RBNG-GVNK. Centraal Bureau voor de Statistiek.
Cai, Mingyang, Stef van Buuren, and Gerko Vink. 2023. “Graphical and Numerical Diagnostic Tools to Assess Multiple Imputation Models by Posterior Predictive Checking.” Heliyon.
Oberman, Hanne I., and Gerko Vink. 2023. “Toward a Standardized Evaluation of Imputation Methodology.” Biometrical Journal, 2200107. https://doi.org/https://doi.org/10.1002/bimj.202200107.
Schouten, Rianne Margaretha, and Gerko Vink. 2021. “The Dance of the Mechanisms: How Observed Information Influences the Validity of Missingness Assumptions.” Sociological Methods & Research 50 (3): 1243–58.
Volker, Thom, and Gerko Vink. 2022. “Synthetic Data in r: Generating Synthetic Data with High Utility Using Mice.” Https://Www.gerkovink.com/miceVignettes/Synthetic/Synthetic.html.


Plain text:

::: {#refs}
:::

Putting it all together

Image placement

A surfing elephant

The above figure is left-aligned
The caption is also left-aligned

A surfing elephant

The above figure is centered
The caption is still left-aligned

The code for the figures is

![A surfing elephant](images/lec-2/elephantastic.png){fig-align="left"}
![A surfing elephant](images/lec-2/elephantastic.png){fig-align="center"}

Columns, sizing, equations and proper centering

A surfing \(\epsilon\lambda\epsilon\phi h\alpha\nu\tau\)

\(e^{i\pi} + 1 = 0\)

The above figure is left-aligned
The caption is also left-aligned
The equation is left-aligned too

A surfing elephant

\[e^{i\pi} + 1 = 0\]

The above figure is centered
The caption is also centered
The equation is centered

The code for the slide is

## Columns, Sizing, Equations and proper centering

::: columns
::: {.column width="50%"}
![A surfing $\epsilon\lambda\epsilon\phi h\alpha\nu\tau$](images/lec-2/elephantastic.png){fig-align="left" width="80%"}

$e^{i\pi} + 1 = 0$

The above figure is left-aligned <br>
The caption is also left-aligned <br>
The equation is left-aligned too
:::

::: {.column width="50%"}
<center>
![A surfing elephant](images/lec-2/elephantastic.png){fig-align="center" width="80%"}
</center>

$$e^{i\pi} + 1 = 0$$

The above figure is centered <br>
The caption is also centered <br>
The equation is centered
:::

:::

The code for the slide is

``` markdown
## Columns, Sizing, Equations and proper centering

::: columns
::: {.column width="50%"}
![A surfing $\epsilon\lambda\epsilon\phi h\alpha\nu\tau$](images/lec-2/elephantastic.png){fig-align="left" width="80%"}

$e^{i\pi} + 1 = 0$

The above figure is left-aligned <br>
The caption is also left-aligned <br>
The equation is left-aligned too
:::

::: {.column width="50%"}
<center>
![A surfing elephant](images/lec-2/elephantastic.png){fig-align="center" width="80%"}
</center>

$$e^{i\pi} + 1 = 0$$

The above figure is centered <br>
The caption is also centered <br>
The equation is centered
:::

:::

F-ing it all up

Rick taking a bath

\(e^{i\pi} + 1 = 0\)

The above figure is left-aligned
The caption is also left-aligned
The equation is left-aligned too

Rick taking a bath

\[e^{i\pi} + 1 = 0\]

The above figure is centered
The caption is also centered
The equation is centered

::: columns
::: {.column width="70%"}
![Rick taking a bath](images/lec-2/bathrick.png){fig-align="left" width="70%"}

$e^{i\pi} + 1 = 0$

:::

::: {.column width="30%"}
<center>
![Rick taking a bath](images/lec-2/bathrick.png){fig-align="center" width="30%"}
</center>

$$e^{i\pi} + 1 = 0$$
:::

:::

Math-ing it all up

Rick taking a bath

\(e^{i\pi} + 1 = 0\)

Rick taking a bath

\[e^{i\pi} + 1 = 0\]

## Math-ing it all up
::: columns
::: {.column width="70%"}
![Rick taking a bath](images/lec-2/goodrick.png){fig-align="left" width="30%"}

$e^{i\pi} + 1 = 0$
:::

::: {.column width="30%"}
<center>
![Rick taking a bath](images/lec-2/goodrick.png){fig-align="center" width="70%"}
</center>

$$e^{i\pi} + 1 = 0$$
:::

:::

```markdown
END OF EXAMPLE

Code chunks

We already saw some markdown code chunks. We can run inline code to calculate that 12 * 234 is 2808 by using `r ` and code chunks to evaluate larger blocks of code, such as:

Code 
library(ggplot2)

ggplot(mpg, aes(x = hwy, y = cty, color = cyl)) +
  geom_point(alpha = 0.5, size = 2) +
  scale_color_viridis_c() +
  theme_minimal()

ggplot(mpg, aes(x = hwy, y = cty, color = displ)) +
  geom_point(alpha = 0.5, size = 2) +
  scale_color_viridis_c(option = "E") +
  theme_minimal()
(a) Color by number of cylinders
(b) Color by engine displacement, in liters
Figure 2: City and highway mileage for 38 popular models of cars.

The previous slide

## Code chunks and explicit caching

```{r}
#| output: asis

answer <- 12 * 234
``` 

We already saw some `markdown` code chunks. We can run inline code to calculate 
that `12 * 234` is ` r answer ` by using `r  ` and code chunks to evaluate 
larger blocks of code, such as:


```{{r}}
#| output: asis
#| label: fig-mpg
#| fig-cap: "City and highway mileage for 38 popular models of cars."
#| fig-subcap:
#|   - "Color by number of cylinders"
#|   - "Color by engine displacement, in liters"
#| layout-ncol: 2
#| column: page
#| code-fold: true
library(ggplot2)

ggplot(mpg, aes(x = hwy, y = cty, color = cyl)) +
  geom_point(alpha = 0.5, size = 2) +
  scale_color_viridis_c() +
  theme_minimal()

ggplot(mpg, aes(x = hwy, y = cty, color = displ)) +
  geom_point(alpha = 0.5, size = 2) +
  scale_color_viridis_c(option = "E") +
  theme_minimal()
```

Explicit Caching

  • Explicit caching is a technique used in RMarkdown and Quarto documents to store and reuse the results of expensive computations or data processing steps.
  • It helps improve the efficiency of document generation and ensures reproducibility by avoiding redundant calculations.

Why Use Explicit Caching?

  • Efficiency: Caching saves time and resources by avoiding the repeated execution of time-consuming code chunks.

  • Reproducibility: Explicit caching ensures that the same results are used when rendering the document, even if the code is modified or re-executed.

  • Version Control: Caching reduces the size of version-controlled documents by storing intermediate results separately.

How Does Explicit Caching Work?

  • In RMarkdown and Quarto, you can use cache directives to specify which code chunks should be cached and which should not.

  • Cached chunks are identified by a unique hash based on their code content, ensuring consistency.

The following code block

```{r}
#| echo: false
#| cache: true
#| code-line-numbers: true
#| label: imputation
library(mice)
library(purrr)
imp <- nhanes |> mice(print = FALSE)
imp |>
  complete("all") |> 
  map(~lm(bmi ~ chl + hyp, data = .x)) |>
  pool()
```

would result in this output

Class: mipo    m = 5 
         term m    estimate         ubar            b            t dfcom
1 (Intercept) 5 21.27602717 18.759034078 2.413095e+00 2.165475e+01    22
2         chl 5  0.03133399  0.000449016 7.865769e-05 5.434052e-04    22
3         hyp 5 -0.81540952  3.747114358 9.352609e-01 4.869427e+00    22
        df       riv    lambda       fmi
1 16.25906 0.1543637 0.1337219 0.2236825
2 14.85089 0.2102135 0.1736995 0.2662776
3 12.90561 0.2995140 0.2304815 0.3272422

with corresponding cache structure relative to the root and format of the output file:

Reproducibility

\(\rightarrow\) topic lecture 4

  • Reproducible examples
  • Reproducible environments

reprex and renv

library(renv)
#> 
#> Attaching package: 'renv'
#> The following objects are masked from 'package:stats':
#> 
#>     embed, update
#> The following objects are masked from 'package:utils':
#> 
#>     history, upgrade
#> The following objects are masked from 'package:base':
#> 
#>     autoload, load, remove
renv::init()
#> - Linking packages into the project library ... Done!
#> The following package(s) will be updated in the lockfile:
#> 
#> # CRAN -----------------------------------------------------------------------
#> - backports       [* -> 1.4.1]
#> - base64enc       [* -> 0.1-3]
#> - broom           [* -> 1.0.4]
#> - bslib           [* -> 0.4.2]
#> - cachem          [* -> 1.0.8]
#> - cli             [* -> 3.6.1]
#> - cpp11           [* -> 0.4.3]
#> - digest          [* -> 0.6.31]
#> - dplyr           [* -> 1.1.2]
#> - ellipsis        [* -> 0.3.2]
#> - evaluate        [* -> 0.21]
#> - fansi           [* -> 1.0.4]
#> - fastmap         [* -> 1.1.1]
#> - fontawesome     [* -> 0.5.1]
#> - fs              [* -> 1.6.2]
#> - generics        [* -> 0.1.3]
#> - glue            [* -> 1.6.2]
#> - highr           [* -> 0.10]
#> - htmltools       [* -> 0.5.5]
#> - jquerylib       [* -> 0.1.4]
#> - jsonlite        [* -> 1.8.4]
#> - knitr           [* -> 1.43]
#> - lattice         [* -> 0.21-8]
#> - lifecycle       [* -> 1.0.3]
#> - magrittr        [* -> 2.0.3]
#> - memoise         [* -> 2.0.1]
#> - mime            [* -> 0.12]
#> - pillar          [* -> 1.9.0]
#> - pkgconfig       [* -> 2.0.3]
#> - purrr           [* -> 1.0.1]
#> - R6              [* -> 2.5.1]
#> - rappdirs        [* -> 0.3.3]
#> - Rcpp            [* -> 1.0.11]
#> - RcppArmadillo   [* -> 0.12.4.0.0]
#> - renv            [* -> 1.0.2]
#> - rlang           [* -> 1.1.1]
#> - rmarkdown       [* -> 2.22]
#> - sass            [* -> 0.4.6]
#> - stringi         [* -> 1.7.12]
#> - stringr         [* -> 1.5.0]
#> - tibble          [* -> 3.2.1]
#> - tidyr           [* -> 1.3.0]
#> - tidyselect      [* -> 1.2.0]
#> - tinytex         [* -> 0.45]
#> - utf8            [* -> 1.2.3]
#> - vctrs           [* -> 0.6.2]
#> - withr           [* -> 2.5.0]
#> - xfun            [* -> 0.39]
#> - yaml            [* -> 2.3.7]
#> 
#> # GitHub ---------------------------------------------------------------------
#> - mice            [* -> gerkovink/mice@match_conditional]
#> 
#> The version of R recorded in the lockfile will be updated:
#> - R               [* -> 4.3.0]
#> 
#> - Lockfile written to "/private/var/folders/yx/6rn4qpl13wsgk4c7s3jc9d1r0000gp/T/RtmpMqetyA/reprex-1233f6d959b19-drear-kitty/renv.lock".
library(mice)
#> 
#> Attaching package: 'mice'
#> The following object is masked from 'package:stats':
#> 
#>     filter
#> The following objects are masked from 'package:base':
#> 
#>     cbind, rbind
library(magrittr)
library(purrr)
#> 
#> Attaching package: 'purrr'
#> The following object is masked from 'package:magrittr':
#> 
#>     set_names
#> The following object is masked from 'package:renv':
#> 
#>     modify
renv::snapshot()
#> - The lockfile is already up to date.
renv::remove("mice")
#> - Removing package(s) from project library ...
#> Removing package 'mice' ... Done!
renv::restore()
#> The following package(s) will be updated:
#> 
#> # GitHub ---------------------------------------------------------------------
#> - mice   [* -> gerkovink/mice@match_conditional]
#> 
#> # Installing packages --------------------------------------------------------
#> - Installing mice ...                           OK [linked from cache]
imp <- nhanes |> mice(print = FALSE)
imp |>
  complete("all") |> 
  map(~.x %$% lm(bmi ~ chl + hyp)) |>
  pool()
#> Class: mipo    m = 5 
#>          term m   estimate         ubar            b            t dfcom
#> 1 (Intercept) 5 20.6687887 2.020809e+01 8.8963873222 3.088375e+01    22
#> 2         chl 5  0.0354435 5.409979e-04 0.0001081414 6.707676e-04    22
#> 3         hyp 5 -0.8447582 4.353337e+00 0.9275040571 5.466342e+00    22
#>          df       riv    lambda       fmi
#> 1  9.489411 0.5282868 0.3456725 0.4504537
#> 2 14.161181 0.2398710 0.1934645 0.2874598
#> 3 13.811544 0.2556671 0.2036105 0.2983537

sessionInfo()
#> R version 4.3.0 (2023-04-21)
#> Platform: aarch64-apple-darwin20 (64-bit)
#> Running under: macOS Ventura 13.6
#> 
#> Matrix products: default
#> BLAS:   /Library/Frameworks/R.framework/Versions/4.3-arm64/Resources/lib/libRblas.0.dylib 
#> LAPACK: /Library/Frameworks/R.framework/Versions/4.3-arm64/Resources/lib/libRlapack.dylib;  LAPACK version 3.11.0
#> 
#> locale:
#> [1] en_US.UTF-8/en_US.UTF-8/en_US.UTF-8/C/en_US.UTF-8/en_US.UTF-8
#> 
#> time zone: Europe/Amsterdam
#> tzcode source: internal
#> 
#> attached base packages:
#> [1] stats     graphics  grDevices utils     datasets  methods   base     
#> 
#> other attached packages:
#> [1] purrr_1.0.1    magrittr_2.0.3 mice_3.15.3    renv_1.0.2    
#> 
#> loaded via a namespace (and not attached):
#>  [1] vctrs_0.6.2      cli_3.6.1        knitr_1.43       rlang_1.1.1     
#>  [5] xfun_0.39        generics_0.1.3   glue_1.6.2       backports_1.4.1 
#>  [9] htmltools_0.5.5  fansi_1.0.4      rmarkdown_2.22   grid_4.3.0      
#> [13] evaluate_0.21    tibble_3.2.1     fastmap_1.1.1    yaml_2.3.7      
#> [17] lifecycle_1.0.3  compiler_4.3.0   dplyr_1.1.2      fs_1.6.2        
#> [21] pkgconfig_2.0.3  Rcpp_1.0.11      tidyr_1.3.0      rstudioapi_0.14 
#> [25] lattice_0.21-8   digest_0.6.31    R6_2.5.1         tidyselect_1.2.0
#> [29] reprex_2.0.2     utf8_1.2.3       pillar_1.9.0     tools_4.3.0     
#> [33] withr_2.5.0      broom_1.0.4

Created on 2023-09-27 with reprex v2.0.2

Benefits of Using renv

  • 1. Dependency Isolation: renv creates a dedicated environment for each project, preventing conflicts between package versions.

  • 2. Reproducibility: With renv, you can capture and record the specific package versions used in your project, ensuring reproducibility over time.

  • 3. Collaboration: Share your project with others, and they can easily recreate the same environment using renv.lock.

  • 4. Easier Package Installation: renv simplifies package installation. Just run renv::restore() to set up the project environment.

  • 5. Automatic Snapshot: renv automatically generates a renv.lock file, listing all package versions used, making it easy to recreate the environment.

  • 6. Compatibility: renv is compatible with popular version control systems like Git, facilitating collaboration and sharing.

Use renv::snapshot() to update the renv.lock file when you add or update packages. You can use renv::activate() and renv::deactivate() to activate or deactivate renv for your project.

Scientific publishing with rticles and Quarto

To use rticles from RStudio, you can access the templates through File -> New File -> R Markdown. This will open the dialog box where you can select from one of the available templates:

The quarto use template command can be used to create an article from one the below formats.

Terminal
quarto use template quarto-journals/acm
quarto use template quarto-journals/plos
quarto use template quarto-journals/elsevier
quarto use template quarto-journals/acs
quarto use template quarto-journals/jss

Take aways

  • Quarto markdown is tool to integrate text, figures, code and output
  • Quarto enables data scientists/statisticians to communicate (re)productively
  • There is a universe of plugins and add-ons to make your academic life easier