Last updated: 2021-08-31
Checks: 2 0
Knit directory: proxyMR/
This reproducible R Markdown analysis was created with workflowr (version 1.6.2). The Checks tab describes the reproducibility checks that were applied when the results were created. The Past versions tab lists the development history.
Great! Since the R Markdown file has been committed to the Git repository, you know the exact version of the code that produced these results.
Great! You are using Git for version control. Tracking code development and connecting the code version to the results is critical for reproducibility.
The results in this page were generated with repository version b849be4. See the Past versions tab to see a history of the changes made to the R Markdown and HTML files.
Note that you need to be careful to ensure that all relevant files for the analysis have been committed to Git prior to generating the results (you can use wflow_publish or wflow_git_commit). workflowr only checks the R Markdown file, but you know if there are other scripts or data files that it depends on. Below is the status of the Git repository when the results were generated:
Ignored files:
Ignored: .DS_Store
Ignored: .Rproj.user/
Ignored: fig_test.RData
Ignored: figures_grid_plus_legend.RData
Ignored: household_MR_exhaustive_summary.rds
Ignored: proxyMR_comparison.RData
Ignored: proxyMR_figure_data.RData
Ignored: renv/library/
Ignored: renv/local/
Ignored: renv/staging/
Ignored: summary.RData
Ignored: traits_corr2_update.rds
Untracked files:
Untracked: R/proxyMR_figures.R
Untracked: R/proxyMR_hiercharchy.R
Unstaged changes:
Modified: R/functions.R
Modified: analysis/update_meeting_14_06_2021.Rmd
Modified: analysis/update_meeting_14_07_2021.Rmd
Modified: analysis/update_meeting_25_08_2021.Rmd
Note that any generated files, e.g. HTML, png, CSS, etc., are not included in this status report because it is ok for generated content to have uncommitted changes.
These are the previous versions of the repository in which changes were made to the R Markdown (analysis/index.Rmd) and HTML (docs/index.html) files. If you’ve configured a remote Git repository (see ?wflow_git_remote), click on the hyperlinks in the table below to view the files as they were in that past version.
| File | Version | Author | Date | Message |
|---|---|---|---|---|
| Rmd | b849be4 | jennysjaarda | 2021-08-31 | clean up some website docs |
| html | b849be4 | jennysjaarda | 2021-08-31 | clean up some website docs |
| html | a55da5b | jennysjaarda | 2021-07-22 | Build site. |
| Rmd | b0b81d9 | jennysjaarda | 2021-07-22 | Updating website |
| html | 021aeb8 | jennysjaarda | 2021-06-18 | Build site. |
| html | b02d111 | jennysjaarda | 2021-06-18 | Build site. |
| Rmd | e1aeb5f | jennysjaarda | 2021-06-02 | Start workflowr project. |
This is the website for the research project “proxyMR”.
If you have cloned the project to a local computer this website is rendered in the docs subdirectory of the project directory.
If you are using workflowr to publish the research website it will also be rendered online to GitHub Pages.
This page acts as a table of contents for the website. There are links to the web pages generated from the analysis notebooks and to the rendered versions of manuscripts/documents/presentations.
This notebook explains the central ideas behind the project.
This notebook is for keeping notes of any points that may be useful for later project or manuscript development and which are not covered in the analysis notebooks or at risk of getting lost in the notebooks.
This project uses the targets and workflowr packages for managing the workflow of the project (making sure that the dependencies between computational steps are satisfied). This notebook contains notes on the proposed workflow for using targets and workflowr.
This notebook displays the computational status of the project, that is, whether everything is up to date. Ironically, this is currently the only notebook that must be run manually, so this notebook only displays the status when the notebook was last executed and there is no indication whether the project status has changed since then.
Links to rendered manuscripts and presentations will go here.
These notebooks capture the analyses that were carried out to develop the code of the core processing pipeline. They are organised as side-chains to the core processing pipeline.
Typically, a meta notebook will analyse the data available at one stage of the core pipeline, to guide the writing of the functions required to get to the next stage of the core pipeline. These meta notebooks generally conclude with the definition of a function that will be used in the core pipeline.
There may be multiple notebooks all relating to different aspects of the same stage of the core pipeline.
Sometimes the analyses are more diffuse - characterising the data in a way that may be helpful for guiding the development of future core stages, but not immediately resulting in the development of functions for the core pipeline.
Determine the initial data preparation of the imported entity records.
Read the raw entity data.
Apply the row exclusions (exclude test records and all records with status other than ACTIVE & VERIFIED).
Drop variables with no variation.
Parse the date columns.
Check the administrative variables (data relating to the administration of voter registration).
Check the residence variables - residential address and phone number.
Check the demographic variables - sex, age, and birth place.
Check the name variables.
Primary analysis performed by: Jenny Sjaarda.
Project supervisor: Professor Zoltan Kutalik.
This work has been supported by the Swiss National Science Foundation.