Last updated: 2021-11-14

Checks: 7 0

Knit directory: 2019-feature-selection/

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.

R Markdown file: up-to-date

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.

Environment: empty

Great job! The global environment was empty. Objects defined in the global environment can affect the analysis in your R Markdown file in unknown ways. For reproduciblity it’s best to always run the code in an empty environment.

Seed: set.seed(20190522)

The command set.seed(20190522) was run prior to running the code in the R Markdown file. Setting a seed ensures that any results that rely on randomness, e.g. subsampling or permutations, are reproducible.

Session information: recorded

Great job! Recording the operating system, R version, and package versions is critical for reproducibility.

Cache: none

Nice! There were no cached chunks for this analysis, so you can be confident that you successfully produced the results during this run.

File paths: relative

Great job! Using relative paths to the files within your workflowr project makes it easier to run your code on other machines.

Repository version: 5d20824

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 5d20824. 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:    .Rhistory
    Ignored:    .Rproj.user/
    Ignored:    .Ruserdata/
    Ignored:    .drake/
    Ignored:    .vscode/
    Ignored:    analysis/rosm.cache/
    Ignored:    data/
    Ignored:    inst/Benchmark for Filter Methods for Feature Selection in High-Dimensional  Classification Data.pdf
    Ignored:    inst/study-area-map/._study-area.qgs
    Ignored:    inst/study-area-map/study-area.qgs~
    Ignored:    log/
    Ignored:    renv/library/
    Ignored:    renv/local/
    Ignored:    renv/staging/
    Ignored:    reviews/
    Ignored:    rosm.cache/

Unstaged changes:
    Modified:   _drake.R
    Modified:   code/070-benchmark-matrix.R

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/eval-performance.Rmd) and HTML (docs/eval-performance.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 5d20824 pat-s 2021-11-14 wflow_publish(knitr_in(“analysis/eval-performance.Rmd”), view = FALSE,
html ec823dc pat-s 2021-11-13 Build site.
html 86f82f8 pat-s 2021-11-12 Merge branch ‘main’ of github.com:pat-s/2019-feature-selection into main
html 1fec32a pat-s 2021-11-12 Build site.
Rmd a82aa75 pat-s 2021-11-06 Merge branch ‘main’ of github.com:pat-s/2019-feature-selection
html a82aa75 pat-s 2021-11-06 Merge branch ‘main’ of github.com:pat-s/2019-feature-selection
Rmd 2d9094f pat-s 2021-11-06 chmod 644 -> 755
html 2d9094f pat-s 2021-11-06 chmod 644 -> 755
html e960beb pat-s 2021-11-02 Build site.
Rmd cf8f5bd pat-s 2021-11-02 wflow_publish(knitr_in(“analysis/eval-performance.Rmd”), view = FALSE,
html 30633b5 pat-s 2021-10-31 Build site.
Rmd 69be3f3 pat-s 2021-10-31 wflow_publish(knitr_in(“analysis/eval-performance.Rmd”), view = FALSE,
html bb69f7b pat-s 2021-09-02 Build site.
Rmd 886ccca pat-s 2021-09-02 wflow_publish(knitr_in(“analysis/eval-performance.Rmd”), view = FALSE,
html c2152bf pat-s 2021-09-02 Build site.
Rmd 28e71ba pat-s 2021-09-02 wflow_publish(knitr_in(“analysis/eval-performance.Rmd”), view = FALSE,
html fc4dcb2 pat-s 2021-08-24 Build site.
Rmd d88d4f6 pat-s 2021-08-24 wflow_publish(knitr_in(“analysis/eval-performance.Rmd”), view = FALSE,
html c56ffc4 pat-s 2021-08-18 Build site.
Rmd cad7668 pat-s 2021-08-18 wflow_publish(knitr_in(“analysis/eval-performance.Rmd”), view = FALSE,
html 5143f3c pat-s 2021-06-28 Build site.
Rmd 861ccc0 pat-s 2021-06-28 workflowr::wflow_publish(“analysis/eval-performance.Rmd”)
html d4267fd pat-s 2021-06-24 Build site.
html b24002a pat-s 2021-06-22 Build site.
Rmd bf76e50 pat-s 2021-06-22 update eval performance plots
html 71e6cf3 pat-s 2021-06-21 docs
Rmd 1177b23 pat-s 2021-06-21 upd tuning table
Rmd c9a19ef pat-s 2021-06-21 upd feature sel table caption
html 2c8ad62 pat-s 2021-06-11 Build site.
Rmd 3f9cb9a pat-s 2021-06-11 wflow_publish(knitr_in(“analysis/eval-performance.Rmd”), view = FALSE,
html a2ae523 pat-s 2021-04-29 Build site.
Rmd efbf354 pat-s 2021-04-29 wflow_publish(knitr_in(“analysis/eval-performance.Rmd”), view = FALSE,
html 1683d67 pat-s 2021-04-12 Build site.
Rmd 48579a4 pat-s 2021-04-12 wflow_publish(knitr_in(“analysis/eval-performance.Rmd”), view = FALSE,
html 91429d5 pat-s 2021-04-10 Build site.
Rmd c7bcae0 pat-s 2021-04-10 wflow_publish(knitr_in(“analysis/eval-performance.Rmd”), view = FALSE,
html 759a0d6 pat-s 2021-04-09 Build site.
Rmd fd1b47e pat-s 2021-04-09 wflow_publish(knitr_in(“analysis/eval-performance.Rmd”), view = FALSE,
html 6bec2b4 pat-s 2021-04-09 Build site.
Rmd 2b8414c pat-s 2021-04-09 fix beeswarm plots
html d63a11c pat-s 2021-04-06 Build site.
Rmd 7cc26f7 pat-s 2021-03-29 wflow_publish(knitr_in(“analysis/eval-performance.Rmd”), view = FALSE,
html 67007fc pat-s 2021-03-29 Build site.
Rmd 85bffd2 pat-s 2021-03-29 wflow_publish(knitr_in(“analysis/eval-performance.Rmd”), view = FALSE,
html 0bb65fb pat-s 2021-03-29 Build site.
Rmd 4bebb61 pat-s 2021-03-29 wflow_publish(knitr_in(“analysis/eval-performance.Rmd”), view = FALSE,
Rmd 7e19df7 pat-s 2021-03-07 fix plot order in eval-performance
html b2ac43b pat-s 2021-02-20 Build site.
html a953299 pat-s 2020-08-12 Build site.
html 8b5e422 pat-s 2020-08-05 Build site.
html 6f88553 pat-s 2020-06-21 Build site.
Rmd c94e7fc pat-s 2020-06-21 wflow_publish(knitr_in(“analysis/eval-performance.Rmd”), view = FALSE,
html 9a54378 pat-s 2020-05-29 Build site.
Rmd 679a87a pat-s 2020-05-29 wflow_publish(knitr_in(“analysis/eval-performance.Rmd”), view = FALSE,
html 6eeb69b pat-s 2020-05-06 Build site.
Rmd fc28c0f pat-s 2020-05-06 wflow_publish(knitr_in(“analysis/eval-performance.Rmd”), view = FALSE,
html a2a6562 pat-s 2020-05-03 Build site.
Rmd b9d07a0 pat-s 2020-05-03 wflow_publish(knitr_in(“analysis/eval-performance.Rmd”), view = FALSE,
html f7737ce pat-s 2020-04-30 Build site.
Rmd 576a62f pat-s 2020-04-30 wflow_publish(knitr_in(“analysis/eval-performance.Rmd”), view = FALSE,
html fcabe1a pat-s 2020-04-30 Build site.
Rmd 3aa1860 pat-s 2020-04-30 wflow_publish(knitr_in(“analysis/eval-performance.Rmd”), view = FALSE,
html bf3eee4 pat-s 2020-04-30 Build site.
Rmd 3a4a1ae pat-s 2020-04-30 wflow_publish(knitr_in(“analysis/eval-performance.Rmd”), view = FALSE,
html ebf4147 pat-s 2020-04-30 Build site.
Rmd 96f47c3 pat-s 2020-04-30 wflow_publish(knitr_in(“analysis/eval-performance.Rmd”), view = FALSE,
html 1c1c5f4 pat-s 2020-04-30 Build site.
Rmd b1d64ea pat-s 2020-04-30 wflow_publish(knitr_in(“analysis/eval-performance.Rmd”), view = FALSE,
html 9ea0dff pat-s 2020-04-29 Build site.
Rmd ba54b0d pat-s 2020-04-29 wflow_publish(knitr_in(“analysis/eval-performance.Rmd”), view = FALSE,
html 3bdb92f pat-s 2020-04-29 Build site.
Rmd 1b98cdd pat-s 2020-04-29 wflow_publish(knitr_in(“analysis/eval-performance.Rmd”), view = FALSE,
html 01b8c74 pat-s 2020-04-29 Build site.
Rmd c79c23d pat-s 2020-04-29 wflow_publish(knitr_in(“analysis/eval-performance.Rmd”), view = FALSE,
html e20d376 pat-s 2020-04-29 Build site.
Rmd 4c8c633 pat-s 2020-04-29 wflow_publish(knitr_in(“analysis/eval-performance.Rmd”), view = FALSE,
html 72c4b82 pat-s 2020-04-19 Build site.
html 89adb44 pat-s 2020-04-18 Build site.
Rmd 6b863d0 pat-s 2020-04-18 wflow_publish(knitr_in(“analysis/eval-performance.Rmd”), view = FALSE,
html 07fb043 pat-s 2020-04-18 Build site.
Rmd abc2b51 pat-s 2020-04-18 wflow_publish(knitr_in(“analysis/eval-performance.Rmd”), view = FALSE,
html e670acc pat-s 2020-04-18 Build site.
Rmd 1fc0c78 pat-s 2020-04-18 wflow_publish(knitr_in(“analysis/eval-performance.Rmd”), view = FALSE,
html 1d1bee4 pat-s 2020-04-18 Build site.
Rmd f3103fc pat-s 2020-04-18 wflow_publish(knitr_in(“analysis/eval-performance.Rmd”), view = FALSE,
html 4982c76 pat-s 2020-04-18 Build site.
Rmd b4fda43 pat-s 2020-04-18 wflow_publish(knitr_in(“analysis/eval-performance.Rmd”), view = FALSE,
html 6c42b7c pat-s 2020-04-18 Build site.
Rmd 8c30483 pat-s 2020-04-18 wflow_publish(knitr_in(“analysis/eval-performance.Rmd”), view = FALSE,
html 544e288 pat-s 2020-04-12 Build site.
Rmd ce72956 pat-s 2020-04-12 wflow_publish(knitr_in(“analysis/eval-performance.Rmd”), view = FALSE,
html 6bded83 pat-s 2020-03-05 Build site.
Rmd 21453cb pat-s 2020-03-05 wflow_publish(knitr_in(“analysis/eval-performance.Rmd”), view = FALSE,
html f59d02a pat-s 2020-03-05 Build site.
Rmd 167fdbc pat-s 2020-03-05 wflow_publish(knitr_in(“analysis/eval-performance.Rmd”), view = FALSE,
html 2ee982d pat-s 2020-03-05 Build site.
Rmd d487d51 pat-s 2020-03-05 wflow_publish(knitr_in(“analysis/eval-performance.Rmd”), view = FALSE,
html 776b35f pat-s 2020-03-03 Build site.
Rmd d0c645a pat-s 2020-03-03 wflow_publish(knitr_in(“analysis/eval-performance.Rmd”), view = FALSE,
html 274a918 pat-s 2020-02-25 Build site.
Rmd 2e632e1 pat-s 2020-02-25 wflow_publish(knitr_in(“analysis/eval-performance.Rmd”), view = FALSE,
Rmd a53ea68 pat-s 2020-02-24 add prefixes to plots and tables
Rmd 379bd5d pat-s 2020-02-24 wflow_publish(knitr_in(“analysis/eval-performance.Rmd”), view = FALSE,
html f680221 pat-s 2020-01-15 Build site.
html b25e779 pat-s 2020-01-10 Build site.
Rmd db0baaa pat-s 2020-01-10 wflow_publish(knitr_in(“analysis/eval-performance.Rmd”), view = FALSE,
html 7f9507f pat-s 2019-12-10 Build site.
Rmd 951e98c pat-s 2019-12-10 wflow_publish(knitr_in(“analysis/eval-performance.Rmd”), view = FALSE, verbose =
Rmd b27c623 pat-s 2019-12-09 Standard Error -> SE
Rmd 559a59d pat-s 2019-12-09 add scatterplots to vis BM perf
html 482a158 pat-s 2019-11-01 Build site.
html becf5ea pat-s 2019-11-01 Build site.
html bd7c7f5 pat-s 2019-10-31 Build site.
html 62ff96f pat-s 2019-10-07 Build site.
html a947654 pat-s 2019-10-02 Build site.
html 49da171 pat-s 2019-09-22 Build site.
html c6317a8 pat-s 2019-09-19 Build site.
Rmd d7c72a8 pat-s 2019-09-19 wflow_publish(knitr_in(“analysis/eval-performance.Rmd”), view = FALSE,
html 7fd40ca pat-s 2019-09-18 Build site.
Rmd 44ff84b pat-s 2019-09-18 wflow_publish(knitr_in(“analysis/eval-performance.Rmd”), view = FALSE,
html 41aae14 pat-s 2019-09-12 Build site.
html ff340b8 pat-s 2019-09-03 Build site.
Rmd a524819 pat-s 2019-09-03 wflow_publish(knitr_in(“analysis/eval-performance.Rmd”), view = FALSE,
html b181c52 pat-s 2019-09-02 Build site.
Rmd cf6e820 pat-s 2019-09-02 wflow_publish(“analysis/eval-performance.Rmd”)
Rmd 1bec10d pat-s 2019-09-01 no timestamps in latex tables
html 4e363ac pat-s 2019-09-01 Build site.
Rmd 518d0cb pat-s 2019-09-01 style files using tidyverse style
html 8e7e4fe pat-s 2019-09-01 Build site.
Rmd 8941bca pat-s 2019-09-01 wflow_publish(knitr_in(“analysis/eval-performance.Rmd”), view = FALSE,
Rmd 297ed93 pat-s 2019-08-31 add filter vs no filter comparison plot
html 7582c67 pat-s 2019-08-31 Build site.
html abd531f pat-s 2019-08-31 Build site.
Rmd 9117eee pat-s 2019-08-31 wflow_publish(knitr_in(“analysis/eval-performance.Rmd”), view = FALSE,
Rmd 5b629cb pat-s 2019-08-19 add new tasks to performance eval report
html 1ec8768 pat-s 2019-08-17 Build site.
html df85aba pat-s 2019-07-12 Build site.
html 3a44a95 pat-s 2019-07-10 Build site.
html c238ce4 pat-s 2019-07-10 Build site.
Rmd e98cb01 pat-s 2019-07-10 wflow_publish(knitr_in(“analysis/eval-performance.Rmd”), view = FALSE,
Rmd 24e318f pat-s 2019-07-01 update reports
Rmd ca5c5bc pat-s 2019-06-28 add eval-performance report

Last update:

[1] "Sun Nov 14 17:08:53 2021"

Fold performances of “SVM MBO No Filter” on the HR Task

(Table) T1 All leaner/filter/task combinations ordered by performance.

Overall leaderboard across all settings, sorted ascending by performance.

(Table) T2 Best learner/filter/task combination

Learners: On which task and using which filter did every learner score their best result on?

*CV: L2 penalized regression using the internal 10-fold CV tuning of the glmnet package

*MBO: L2 penalized regression using using MBO for hyperparameter optimization.

(Table) T3 All leaner/filter/task combinations ordered descending by performance.

Overall leaderboard across all settings, sorted descending by performance.

(Plot) P1 Best learner/filter combs for all tasks

Version Author Date
86f82f8 pat-s 2021-11-12
1fec32a pat-s 2021-11-12
a82aa75 pat-s 2021-11-06
2d9094f pat-s 2021-11-06
e960beb pat-s 2021-11-02
c56ffc4 pat-s 2021-08-18
d4267fd pat-s 2021-06-24
b24002a pat-s 2021-06-22
bf76e50 pat-s 2021-06-22
2c8ad62 pat-s 2021-06-11
d63a11c pat-s 2021-04-06
0bb65fb pat-s 2021-03-29
b2ac43b pat-s 2021-02-20
e20d376 pat-s 2020-04-29
07fb043 pat-s 2020-04-18
1d1bee4 pat-s 2020-04-18
6c42b7c pat-s 2020-04-18
544e288 pat-s 2020-04-12
f59d02a pat-s 2020-03-05
2ee982d pat-s 2020-03-05
274a918 pat-s 2020-02-25
b25e779 pat-s 2020-01-10
7f9507f pat-s 2019-12-10
482a158 pat-s 2019-11-01
becf5ea pat-s 2019-11-01
bd7c7f5 pat-s 2019-10-31
62ff96f pat-s 2019-10-07
a947654 pat-s 2019-10-02
49da171 pat-s 2019-09-22
41aae14 pat-s 2019-09-12
b181c52 pat-s 2019-09-02
8e7e4fe pat-s 2019-09-01
7582c67 pat-s 2019-08-31
abd531f pat-s 2019-08-31

(Plot) P2 Scatterplots of filter methods vs. no filter for each learner and task

Showing the final effect of applying feature selection to a learner for each task. All filters are colored in the same way whereas using “no filter” appears in a different color.

Version Author Date
86f82f8 pat-s 2021-11-12
1fec32a pat-s 2021-11-12
2d9094f pat-s 2021-11-06
c56ffc4 pat-s 2021-08-18
d4267fd pat-s 2021-06-24
b24002a pat-s 2021-06-22
2c8ad62 pat-s 2021-06-11
d63a11c pat-s 2021-04-06
0bb65fb pat-s 2021-03-29
b2ac43b pat-s 2021-02-20
e20d376 pat-s 2020-04-29
1d1bee4 pat-s 2020-04-18
6c42b7c pat-s 2020-04-18
544e288 pat-s 2020-04-12
f59d02a pat-s 2020-03-05
2ee982d pat-s 2020-03-05
274a918 pat-s 2020-02-25
b25e779 pat-s 2020-01-10
7f9507f pat-s 2019-12-10

(Plot) P3 Scatterplots of filter methods vs. Borda for each learner and task

Showing the final effect of applying feature selection to a learner for each task. All filters are summarized into a a single color whereas the “Borda” filter appears in its own color.

Version Author Date
86f82f8 pat-s 2021-11-12
1fec32a pat-s 2021-11-12
2d9094f pat-s 2021-11-06
c56ffc4 pat-s 2021-08-18
d4267fd pat-s 2021-06-24
b24002a pat-s 2021-06-22
2c8ad62 pat-s 2021-06-11
6bec2b4 pat-s 2021-04-09
d63a11c pat-s 2021-04-06
0bb65fb pat-s 2021-03-29
b2ac43b pat-s 2021-02-20
e20d376 pat-s 2020-04-29
1d1bee4 pat-s 2020-04-18
6c42b7c pat-s 2020-04-18
544e288 pat-s 2020-04-12
f59d02a pat-s 2020-03-05
2ee982d pat-s 2020-03-05
776b35f pat-s 2020-03-03
274a918 pat-s 2020-02-25
b25e779 pat-s 2020-01-10
7f9507f pat-s 2019-12-10

(Table) T4 Number of features selected during tuning

The model/task combinations which were selected relate to the best performance of the respective algorithm on the HR-NRI-VI task in the overall benchmark.

Fold IDs are different for each learner, i.e. a specific plot does not always resolve to “fold 1” for each learner. See bmr_inspect_tune[["results"]][["hr_nri_vi"]][["RF MBO Relief"]][["pred"]][["instance"]][["test.inds"]].

Thus, we need to manually label the fold IDs to plot names for each learner.

Example for RF on fold 1 (Luiando):

RF

SVM

XGBoost

Aggregated mean and standard deviation:

Warning: Unknown levels in `f`: RF MBO Relief, XGBOOST MBO CMIM, SVM MBO Relief

R version 4.0.4 (2021-02-15)
Platform: x86_64-pc-linux-gnu (64-bit)
Running under: CentOS Linux 7 (Core)

Matrix products: default
BLAS:   /opt/spack/opt/spack/linux-centos7-x86_64/gcc-9.2.0/r-4.0.4-udi7a3ahhtokdcoyqdbndhebeupt7hid/rlib/R/lib/libRblas.so
LAPACK: /opt/spack/opt/spack/linux-centos7-x86_64/gcc-9.2.0/r-4.0.4-udi7a3ahhtokdcoyqdbndhebeupt7hid/rlib/R/lib/libRlapack.so

locale:
 [1] LC_CTYPE=en_US.UTF-8       LC_NUMERIC=C              
 [3] LC_TIME=en_US.UTF-8        LC_COLLATE=en_US.UTF-8    
 [5] LC_MONETARY=en_US.UTF-8    LC_MESSAGES=en_US.UTF-8   
 [7] LC_PAPER=en_US.UTF-8       LC_NAME=C                 
 [9] LC_ADDRESS=C               LC_TELEPHONE=C            
[11] LC_MEASUREMENT=en_US.UTF-8 LC_IDENTIFICATION=C       

attached base packages:
[1] stats     graphics  grDevices datasets  utils     methods   base     

other attached packages:
 [1] forcats_0.5.1     dplyr_1.0.4       mlr_2.19.0.9000   ParamHelpers_1.14
 [5] here_1.0.1        ggpubr_0.4.0      ggrepel_0.9.1     ggsci_2.9        
 [9] ggbeeswarm_0.7.0  ggplot2_3.3.3     flextable_0.6.3   xtable_1.8-4     
[13] usethis_2.0.0     magrittr_2.0.1    drake_7.13.2     

loaded via a namespace (and not attached):
  [1] colorspace_2.0-0   ggsignif_0.6.0     smoof_1.6.0.2     
  [4] ellipsis_0.3.1     rio_0.5.16         rprojroot_2.0.2   
  [7] base64enc_0.1-3    fs_1.5.0           rstudioapi_0.13   
 [10] farver_2.0.3       DT_0.17            xml2_1.3.2        
 [13] splines_4.0.4      R.methodsS3_1.8.1  knitr_1.31        
 [16] mco_1.15.6         jsonlite_1.7.2     workflowr_1.6.2   
 [19] broom_0.7.4        R.oo_1.24.0        mlrMBO_1.1.5      
 [22] compiler_4.0.4     httr_1.4.2         backports_1.2.1   
 [25] Matrix_1.3-2       lazyeval_0.2.2     cli_2.4.0         
 [28] later_1.1.0.1      htmltools_0.5.1.1  prettyunits_1.1.1 
 [31] tools_4.0.4        igraph_1.2.6       misc3d_0.9-0      
 [34] gtable_0.3.0       glue_1.4.2         fastmatch_1.1-0   
 [37] Rcpp_1.0.6         parallelMap_1.5.0  carData_3.0-4     
 [40] cellranger_1.1.0   vctrs_0.3.6        RJSONIO_1.3-1.4   
 [43] crosstalk_1.1.1    xfun_0.20          stringr_1.4.0     
 [46] openxlsx_4.2.3     lifecycle_0.2.0    renv_0.13.2       
 [49] rstatix_0.6.0      scales_1.1.1       hms_1.0.0         
 [52] promises_1.1.1     parallel_4.0.4     plot3D_1.3        
 [55] RColorBrewer_1.1-2 BBmisc_1.11        yaml_2.2.1        
 [58] curl_4.3           gdtools_0.2.3      DiceKriging_1.5.8 
 [61] stringi_1.5.3      highr_0.8          checkmate_2.0.0   
 [64] lhs_1.1.1          filelock_1.0.2     zip_2.1.1         
 [67] storr_1.2.5        rlang_0.4.10       pkgconfig_2.0.3   
 [70] systemfonts_1.0.0  evaluate_0.14      lattice_0.20-41   
 [73] ggbeeswarm2_0.7.0  purrr_0.3.4        labeling_0.4.2    
 [76] htmlwidgets_1.5.3  tidyselect_1.1.0   R6_2.5.0          
 [79] generics_0.1.0     base64url_1.4      txtq_0.2.3        
 [82] pillar_1.4.7       haven_2.3.1        whisker_0.4       
 [85] foreign_0.8-81     withr_2.4.1        abind_1.4-5       
 [88] survival_3.2-7     tibble_3.0.6       crayon_1.4.0      
 [91] car_3.0-10         uuid_0.1-4         plotly_4.9.3      
 [94] rmarkdown_2.6      officer_0.3.16     progress_1.2.2    
 [97] grid_4.0.4         readxl_1.3.1       data.table_1.13.6 
[100] git2r_0.28.0       digest_0.6.27      tidyr_1.1.2       
[103] httpuv_1.5.5       R.utils_2.10.1     munsell_0.5.0     
[106] beeswarm_0.2.3     viridisLite_0.3.0  vipor_0.4.5       
[109] tcltk_4.0.4