You are here: Vanderbilt Biostatistics Wiki>Main Web>Education>StatGraphCourse>RCTGraphics (26 Nov 2019, FrankHarrell)EditAttach

Vanderbilt Department of Biostatistics

Office of Biostatistics FDA CDER

- learn principles of graph construction
- learn which features of summary statistics should be emphasized in a graph
- see examples of increasing information using modern graphics, whether static or interactive
- understand features of html notebooks for statistical reports
- learn how to use
`RStudio`

to make html notebooks - learn to use new functions in the R
`Hmisc`

package which use the R`plotly`

package to produce somewhat interactive graphics - get ideas for constructing your own interactive graphics for statistical reports by seeing examples of placing supplemental information in initially hidden layers of graphics

- providing a more interpretable snapshot of study results
- displaying trends and finding patterns
- speeding up reviews
- displaying data that are too messy to model (e.g., sites within countries within regions)
- displaying marginal (unadjusted) estimates
- replacing tables having many numbers, especially when continuous variables are involved
- showing whole distribution of continuous variables
- finding data problems
- finding problematic data distributions including excessive ties
- displaying results of complex statistical models

- displaying finest levels of details
- providing exact numeric values for elements of graphs

- best way to handle confounding and outcome heterogeneity
- accounts for more variables than any expert could understand in a graph
- handles continuous variables optimally
- handles censoring, incomplete data, large datasets, and heavy ties in data

- Applying Human Factors Research to Statistical Graphics by John Rauser
- Guiding Principles for Effective Data Visualization by William Buchanan
- Why Scientists Need to be Better at Data Visualization by Betsy Mason
- Principles of Graph Construction (see Sections 2.4 and 2.5 for examples related to drug safety)
- Clinical Trial Reports: R+LaTeX+pdf
- Two example reports with source files
- See also this

- R +
`RStudio`

+`Rmarkdown`

+`knitr`

+`plotly`

+ html- R
`Hmisc`

package examples - R
`rms`

package examples (includes plots of predicted values + interactive survival curves)

- R
- R
`hreport`

package: html Clinical Trial Reports:- Example report 1
- Example report 2
- (under development; funded by NIH NCATS CTSA Vanderbilt Institute for Clinical and Translational Research)

- Safety Explorer example (Rmarkdown html notebook)

Authors: Becca Krouse, Spencer Childress, Jeremy Wildfire

Rho, Inc.

- Zip file containing all files above
- Safety Explorer - this can be used in conjunction with the
`hreport`

package,`knitr`

, and`RStudio`

to produce highly interactive tables with small graphics, will drill-down capability from body systems to preferred terms within body systems. A self-contained`html`

report can be produced, and the user interacts without installing any software or using an internet connection. - Flex dashboards for monitoring clinical studies
- Presentation of clinical laboratory results: an experimental comparison of four visualization techniques
- Novel clinical trial graphics by Song, Hsu, Taira
- Tendril plots for AEs
- The design and evaluation of a graphical display for laboratory data
- Graphical summary of patient status by Powsner and Tufte
- http://www.datavisualisation-r.com/
- Effective Displays of Data Need More Attention in Statistics Education by Thomas Bradstreet, Michael Nessly, and Thomas Short
- Graphics for Clinical Trials by Jonathan Levine
- Exploratory Analysis of Clinical Safety Data to Detect Safety Signals (Frank Harrell and Thomas Burgan).
- http://motioninsocial.com/tufte/
- Graphics Principles Cheat Sheet
- Schwarz' Tour of Bad Graphs
- https://www.rstudio.com
- http://rmarkdown.rstudio.com
- http://rmarkdown.rstudio.com/r_notebooks.html
- http://yihui.name/knitr/
- http://biostat.mc.vanderbilt.edu/Hmisc
- http://biostat.mc.vanderbilt.edu/Rrms
- https://plot.ly/r
- https://plot.ly/r/getting-started
- ggplotly: a function that converts any ggplot2 graphic to a plotly interactive graphic: https://plot.ly/ggplot2
- Github Repositories

- Organization: https://github.com/ASA-DIA-InteractiveSafetyGraphics
- eDish Repo with readme: https://github.com/ASA-DIA-InteractiveSafetyGraphics/safety-eDISH
- Interactive eDish example: https://asa-dia-interactivesafetygraphics.github.io/safety-eDISH/test/

- Color palettes: https://www.data-imaginist.com/2018/scico-and-the-colour-conundrum
- Color choices and response times: https://idl.cs.washington.edu/files/2018-QuantitativeColor-CHI.pdf
- What interactives can do (that articles can't) by Elliot Bentley
- Data Visualization by Kieran Healy

Edit | Attach | Print version | History: r28 < r27 < r26 < r25 | Backlinks | View wiki text | Edit wiki text | More topic actions

Topic revision: r28 - 26 Nov 2019, FrankHarrell

Copyright © 2013-2020 by the contributing authors. All material on this collaboration platform is the property of the contributing authors.

Ideas, requests, problems regarding Vanderbilt Biostatistics Wiki? Send feedback

Ideas, requests, problems regarding Vanderbilt Biostatistics Wiki? Send feedback