R Packages and Setup

library(knitr); library(rmdformats)
library(here); library(janitor); library(magrittr)
library(rms); library(broom)

# other packages as needed can go here

library(tidyverse)

1 Data Source

Details, details.

2 The Subjects

3 Loading and Tidying the Data

3.1 Loading the Raw Data

Ingest your raw data here.

3.2 Cleaning the Data

All cleaning and tidying goes here, leading to a single tibble in R. Be sure to explain what you’re doing and why you’re doing it. Do not show listings of the data as you clean it.

3.3 Another Cleaning the Data subheading.

I expect you’ll use several subheadings here to help delineate tasks.

4 The Tidy Tibble

4.1 Listing the Tibble

Here, you will list the tibble, after all cleaning is complete. Just list the tibble.

4.2 Size and Identifiers

Do what we asked you to do in the instructions.

4.3 Saving the R data set

Now, save your tibble as an R data set (.Rds file, which you’ll also provide to us.)

5 The Code Book

See the instructions and be sure that your code book includes all necessary elements.

5.1 Defining the Variables

Here, to help you get started, is the example from the instructions.

Variable Role Type Description
subjectID identifier - character code for subjects
sysbp outcome quant Most Recent Systolic Blood Pressure, in mm Hg
statin input 2-cat Has a current statin prescription? (Yes or No)

5.2 Numerical Description

Here’s where you would run describe from Hmisc.

6 Linear Regression Plans

6.1 My Quantitative Outcome

Follow the instructions.

6.2 My Planned Predictors (Linear Model)

Follow the instructions.

7 Logistic Regression Plans

7.1 My Binary Outcome

Follow the instructions.

7.2 My Planned Predictors (Logistic Model)

Follow the instructions.

8 Affirmation

Be sure to include the text provided in the instructions.

Note that for Task 2 (Analyses and Presentation), we will add in sections called:

  • Linear Regression Modeling
  • Logistic Regression Modeling
  • Discussion

before the Affirmation but otherwise leave the template alone.

9 References

If you are including references, here’s the place for them. You should likely be providing a reference for your data set, at least.

10 Session Information

xfun::session_info()
R version 4.0.3 (2020-10-10)
Platform: x86_64-w64-mingw32/x64 (64-bit)
Running under: Windows 10 x64 (build 19041)

Locale:
  LC_COLLATE=English_United States.1252 
  LC_CTYPE=English_United States.1252   
  LC_MONETARY=English_United States.1252
  LC_NUMERIC=C                          
  LC_TIME=English_United States.1252    

Package version:
  askpass_1.1         assertthat_0.2.1    backports_1.2.1    
  base64enc_0.1-3     BH_1.75.0.0         blob_1.2.1         
  bookdown_0.21       brio_1.1.1          broom_0.7.3        
  callr_3.5.1         cellranger_1.1.0    checkmate_2.0.0    
  cli_2.2.0           clipr_0.7.1         cluster_2.1.0      
  codetools_0.2-16    colorspace_2.0-0    compiler_4.0.3     
  conquer_1.0.2       cpp11_0.2.5         crayon_1.3.4       
  curl_4.3            data.table_1.13.6   DBI_1.1.1          
  dbplyr_2.0.0        desc_1.2.0          diffobj_0.3.3      
  digest_0.6.27       dplyr_1.0.3         ellipsis_0.3.1     
  evaluate_0.14       fansi_0.4.2         farver_2.0.3       
  forcats_0.5.1       foreign_0.8-81      Formula_1.2-4      
  fs_1.5.0            generics_0.1.0      ggplot2_3.3.3      
  glue_1.4.2          graphics_4.0.3      grDevices_4.0.3    
  grid_4.0.3          gridExtra_2.3       gtable_0.3.0       
  haven_2.3.1         here_1.0.1          highr_0.8          
  Hmisc_4.4-2         hms_1.0.0           htmlTable_2.1.0    
  htmltools_0.5.0     htmlwidgets_1.5.3   httr_1.4.2         
  isoband_0.2.3       janitor_2.1.0       jpeg_0.1-8.1       
  jsonlite_1.7.2      knitr_1.31          labeling_0.4.2     
  lattice_0.20-41     latticeExtra_0.6-29 lifecycle_0.2.0    
  lubridate_1.7.9.2   magrittr_2.0.1      markdown_1.1       
  MASS_7.3-53         Matrix_1.2-18       MatrixModels_0.4-1 
  matrixStats_0.57.0  methods_4.0.3       mgcv_1.8.33        
  mime_0.9            modelr_0.1.8        multcomp_1.4-15    
 [ reached getOption("max.print") -- omitted 65 entries ]

11 Notes from Dr. Love

  1. Remember to review the Submission Requirements for the Proposal carefully before you submit your work
  2. Be sure to spellcheck the R Markdown document (just hit F5) and also proofread the HTML result that comes out of this work.
  3. Remove these Notes and any other notes guiding you through this template before you knit the work into an HTML file.