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