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index.qmd
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# Preface {.unnumbered}
This web-book is derived from my lecture slides for Epidemiology 204: "Quantitative Epidemiology III: Statistical Models", at UC Davis.
I have drawn these materials from many sources, including but not limited to:
- [David Rocke](https://dmrocke.ucdavis.edu/)'s materials from the [2021 edition of this course ](https://dmrocke.ucdavis.edu/Class/EPI204-Spring-2021/EPI204-Spring-2021.html)
- [Hua Zhou](https://hua-zhou.github.io/)'s materials from the [2020 edition of Biostat 200C at UCLA](https://ucla-biostat-200c-2020spring.github.io/schedule/schedule.html)
- @vittinghoff2e
- @dobson4e
- @rms2e
## Using these lecture notes {.unnumbered}
These lecture notes are available online at <https://d-morrison.github.io/rme/>.
The online notes are searchable and are currently being iteratively updated^[see the source file repository for recent changes: <https://github.com/d-morrison/rme>].
A pdf version of the notes is also downloadable from <https://d-morrison.github.io/rme/Regression-Models-for-Epidemiology.pdf>,
and the source files are available at <https://github.com/d-morrison/rme>.
### Compiling chapters as lecture slide decks {.unnumbered}
Each chapter's source file can also be compiled as a lecture slide deck, using the
[`_quarto-revealjs.yml`](https://github.com/d-morrison/rme/blob/main/_quarto-revealjs.yml) [Quarto profile](https://quarto.org/docs/projects/profiles.html)
included in the [git repository on Github](https://github.com/d-morrison/rme).
For example, to compile [Chapter @sec-Bernoulli-models] as a slide deck:
1) [install quarto](https://quarto.org/docs/get-started/)
2) clone the project repository from [Github](https://github.com/d-morrison/rme)
3) Install the project dependencies using `devtools`:
``` r
library(devtools) # install from CRAN if needed
devtools::install_deps()
```
4) Render the chapter using the `revealjs` profile using the following terminal shell command:
``` bash
quarto render logistic-regression.qmd --profile=revealjs
```
You can also render all the chapters listed in the [`_quarto-revealjs.yml`](https://github.com/d-morrison/rme/blob/main/_quarto-revealjs.yml)
[Quarto profile](https://quarto.org/docs/projects/profiles.html)
as slide decks simultaneously:
``` bash
quarto render --profile=revealjs
```
---
### Extracting LaTeX commands from the online version of the notes {.unnumbered}
If you want to extract the LaTeX commands for any math expressions in the online lecture notes, you should be able to right-click and get this pop-up menu:
{#fig-right-click-math}
If you select "TeX commands", you will get a window with LaTeX code.^[[MathJax](https://www.mathjax.org/) is more or less a dialect of LaTeX]
{#fig-LaTeX-source-code-popup}
You can also grab the TeX commands from the quarto source files on github, but those files use custom macros (defined in <https://github.com/d-morrison/rme/blob/main/macros.qmd>), so it's a little harder to reuse code from the source files.
---
### Dark Mode {.unnumbered}
The online notes have two color palette themes: light and dark.
You can toggle between them using the oval button near the top-left corner:
{#fig-palette-toggle}
## Other resources {.unnumbered}
These notes represent my still-developing perspective on regression models in epidemiology.
Many other statisticians and epidemiologists have published their own perspectives,
and I encourage you to explore your many options and find ones that resonate with you.
I have attempted to cite my sources throughout these notes.
Here are some additional resources that I've come across;
I haven't had time to read some of them
thoroughly yet, but they're all on my to-do list.
I'll add my thoughts on them over time.
{{< include other-resources.qmd >}}
## License {.unnumbered}
This book is licensed to you under [Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License](http://creativecommons.org/licenses/by-nc-nd/4.0/).
The code samples in this book are licensed under [Creative Commons CC0 1.0 Universal (CC0 1.0)](https://creativecommons.org/publicdomain/zero/1.0/), i.e. public domain.