Reproducibility
Reproducibility
What’s reproducibility?
A different analyst re-performs the analysis with the same code and the same data and obtains the same result.
Reproducibility vs Repeatability vs Replicability
Reproducibility
- Clean your environment regularly
- Use RMarkdown
- Check the knit of your RMarkdown regularly
- Tell your future self and others what you did!
- Print session info!
RMarkdown
Clicking the knit button, will knit your document to create different types of reports. The default is html.
Code Chunks
After knitting:
1) echo - determines if your code should be shown or not
- TRUE = code is shown (default)
- FALSE = code is not shown (but might be run…depends on eval)
2) eval - determines if your code should be evaluated (run) or not
- TRUE = code is run (default)
- FALSE = code is not run (but might be shown…depends on echo)
3) message = FALSE -suppresses messages when your run your code
RMarkdown syntax
Before: 
After knit: 
RMarkdown syntax
Go to File > Help > Cheatsheets > R Markdown Cheatsheet
Final Project
Specific guidelines and example on website
Turn in through CoursePlus:
1) RMarkdown file
2) html file
Session Info
Session info helps
sessionInfo()R version 4.0.5 (2021-03-31)
Platform: x86_64-apple-darwin17.0 (64-bit)
Running under: macOS Big Sur 10.16
Matrix products: default
BLAS: /Library/Frameworks/R.framework/Versions/4.0/Resources/lib/libRblas.dylib
LAPACK: /Library/Frameworks/R.framework/Versions/4.0/Resources/lib/libRlapack.dylib
locale:
[1] en_US.UTF-8/en_US.UTF-8/en_US.UTF-8/C/en_US.UTF-8/en_US.UTF-8
attached base packages:
[1] stats graphics grDevices utils datasets methods base
other attached packages:
[1] forcats_0.5.1 stringr_1.4.0 purrr_0.3.4 tidyr_1.1.3
[5] tibble_3.1.3 ggplot2_3.3.5 tidyverse_1.3.1 dplyr_1.0.7
[9] readr_1.4.0 knitr_1.33
loaded via a namespace (and not attached):
[1] tidyselect_1.1.1 xfun_0.25 bslib_0.3.1 haven_2.4.3
[5] colorspace_2.0-2 vctrs_0.3.8 generics_0.1.0 htmltools_0.5.2
[9] yaml_2.2.1 utf8_1.2.2 rlang_0.4.11 jquerylib_0.1.4
[13] pillar_1.6.2 withr_2.4.2 glue_1.4.2 DBI_1.1.1
[17] dbplyr_2.1.1 modelr_0.1.8 readxl_1.3.1 lifecycle_1.0.0
[21] munsell_0.5.0 gtable_0.3.0 cellranger_1.1.0 rvest_1.0.1
[25] evaluate_0.14 fastmap_1.1.0 fansi_0.5.0 highr_0.9
[29] broom_0.7.10 Rcpp_1.0.7 backports_1.2.1 scales_1.1.1
[33] jsonlite_1.7.2 fs_1.5.0 hms_1.1.0 digest_0.6.27
[37] stringi_1.7.3 grid_4.0.5 cli_3.0.1 tools_4.0.5
[41] magrittr_2.0.1 sass_0.4.0 crayon_1.4.1 pkgconfig_2.0.3
[45] ellipsis_0.3.2 xml2_1.3.2 reprex_2.0.1 lubridate_1.7.10
[49] rstudioapi_0.13 assertthat_0.2.1 rmarkdown_2.10 httr_1.4.2
[53] R6_2.5.1 compiler_4.0.5 DRY code
DRY is an acronym: “Don’t repeat yourself” [@Smith2013].
“I hate code, and I want as little of it as possible in our product.” - Jack Diedrich
More resources
These are just some quick tips, for more information: