estimate: Estimation of Model-Based Predictions, Contrasts and Means

Contribution Guidelines

easystats guidelines 0.1.0

All people are very much welcome to contribute to code, documentation, testing and suggestions.

This package aims at being beginner-friendly. Even if you're new to this open-source way of life, new to coding and github stuff, we encourage you to try submitting pull requests (PRs).

"I'd like to help, but I'm not good enough with programming yet"

It's alright, don't worry! You can always dig in the code, in the documentation or tests. There are always some typos to fix, some docs to improve, some details to add, some code lines to document, some tests to add... Even the smaller PRs are appreciated.

"I'd like to help, but I don't know where to start"

You can look around the issue section to find some features / ideas / bugs to start working on. You can also open a new issue just to say that you're there, interested in helping out. We might have some ideas adapted to your skills.

"I'm not sure if my suggestion or idea is worthwile"

Enough with the impostor syndrom! All suggestions and opinions are good, and even if it's just a thought or so, it's always good to receive feedback.

"Why should I waste my time with this? Do I get any credit?"

Software contributions are getting more and more valued in the academic world, so it is a good time to collaborate with us! Authors of substantial contributions will be added within the authors list. We're also very keen on including them to eventual academic publications.

Anyway, starting is the most important! You will then enter a whole new world, a new fantastic point of view... So fork this repo, do some changes and submit them. We will then work together to make the best out of it :)

Please document and comment your code, so that the purpose of each step (or code line) is stated in a clear and understandable way.
Before submitting a change, please read the R style guide and in particular our easystats convention of code-style to keep some consistency in code formatting.
Regarding the style guide, note this exception: we put readability and clarity before everything. Thus, we like underscores and full names (prefer model_performance over modelperf and interpret_odds_logistic over intoddslog).
Before you start to code, make sure you're on the dev branch (the most "advanced"). Then, you can create a new branch named by your feature (e.g., feature_lightsaber) and do your changes. Finally, submit your branch to be merged into the dev branch. Then, every now and then, the dev branch will merge into master, as a new package version.