From 3957e8c87294cb834a51ea35a3dc30873ea56f7c Mon Sep 17 00:00:00 2001 From: Kyle Husmann Date: Tue, 5 Mar 2024 18:17:48 -0800 Subject: [PATCH] add vignette index to front page --- README.Rmd | 16 ++++++++++++++++ README.md | 17 +++++++++++++++++ 2 files changed, 33 insertions(+) diff --git a/README.Rmd b/README.Rmd index fb89e6f..9eb978c 100644 --- a/README.Rmd +++ b/README.Rmd @@ -37,6 +37,22 @@ as described in `vignette("interlacer")`. (tldr: It allows us to interact with a variable as a [`Result` type](https://en.wikipedia.org/wiki/Result_type), an abstraction often found in functional programming) +Although this may seem like a simple premise on the surface, it has deep +implications! In addition to `vignette("interlacer")`, be sure to also +check out: + +- `vignette("mutations")` for a discussion on how to motify data frames when in +this format + +- `vignette("column-types")` to see how to handle column-level missing reasons + +- `vignette("coded-data")` for some recipies for working with coded data (e.g. +data produced by SPSS, SAS or Stata) + +- `vignette("other-approaches")` for a deep dive into how interlacer's approach +compares to other approaches for representing and manipulating missing reasons +alongside data values + This library is currently in its experimental stages, so be aware that its interface is likely to change in the future. In the meantime, please try it out and diff --git a/README.md b/README.md index 8010130..24be8a2 100644 --- a/README.md +++ b/README.md @@ -26,6 +26,23 @@ interact with a variable as a [`Result` type](https://en.wikipedia.org/wiki/Result_type), an abstraction often found in functional programming) +Although this may seem like a simple premise on the surface, it has deep +implications! In addition to `vignette("interlacer")`, be sure to also +check out: + +- `vignette("mutations")` for a discussion on how to motify data frames + when in this format + +- `vignette("column-types")` to see how to handle column-level missing + reasons + +- `vignette("coded-data")` for some recipies for working with coded data + (e.g. data produced by SPSS, SAS or Stata) + +- `vignette("other-approaches")` for a deep dive into how interlacer’s + approach compares to other approaches for representing and + manipulating missing reasons alongside data values + This library is currently in its experimental stages, so be aware that its interface is likely to change in the future. In the meantime, please try it out and [let me know what you think](mailto:kdh38@psu.edu)!