Downloads

The code that was used to generate the figures in the book is available below.

Note that all code is provided as is. The authors, the editors, and the publisher can not be made responsible for any effects that might be caused by utilizing the code.
Please note also that support can generally not be provided.
However, the authors will be thankful for comments or suggestions.

Section I - General Principles and Reviews of Graphics

1. Concepts and Principles of Clinical Data Graphics Andreas Krause: R code and Excel sheets; The R code is structured as follows:
Each graph is created by a function. The function (for example, of name biomarker.graph) is stored in a file of name biomarker.graph.R.
Entering source("biomarker.graph.R") thus declares the function to R but does not execute it.
Calling biomarker.graph() will run the function and create the graph on the screen. Each function has default arguments such that it can be called without any arguments (!). Data are simulated.
To recreate all R figures, enter
source("000-batch.R")
The figures are all stored in the directory graphs.
Possibly the best way to work through all code is to start looking at the file 000-batch.R. Everything flows from here.
2. Graphics for Exploratory Analysis and Data Discovery in the Life Sciences Michael O'Connell, Ian Cook, Difei Luo and Josh Patel: to come
3. Grables: Visual Displays That Combine the Best Attributes of Graphs and Tables Thomas E. Bradstreet: (Graphs mostly created using the S-PLUS GUI, under investigation if code can be provided)
4. The Use of Figures in Epidemiological Publications: A Survey of Current Practice and Consequent Recommendations Elisabeth Wreford Andersen and Stuart J. Pocock: (not applicable to this chapter due to the nature of it, a review paper)

Section II - Early Clinical Development

5. Use of Graphics for Studies with Small Sample Sizes: A Simulated Case Study of an Early-Phase Asset for Treatment of Type 2 Diabetes Mellitus (T2DM) Denise Shortino, Ann Walker and Andrew Miskell: Zip file including documentation, S-Plus code, data sets
6. Exploring Pharmacokinetic and Pharmacodynamic Data Charles Roosen, Richard Pugh and Andrew Nicholls: The R code can be run as follows: Download the zip file, unzip it, and store it in a directory. Start R in that directory (Windows users can simply click on the .RData file). Enter source("GiLS.R"). Data files are read in and graphics are produced and saved to graphics/output.pdf.
You might need to install additional libraries if you do not have them yet (MSToolkit, reshape, plyr, ggplot2, grid).
In particular, the code was developed using ggplot version 0.9.2.1. Earlier versions stop execution with the error message could not find function "element_rect".
7. (Interactive) Graphics for Biomarker Assessment Michael Merz: Graphs were produced using Spotfire interactively. Thus, no code available but details of the graph creation are provided here.
8. Graphical Displays for Biomarker Data Manuela Zucknick, Thomas Hielscher, Martin Sill and Axel Benner: Documentation, R code, utility functions

Section III - Clinical Trial Graphics

9. Statistical Graphics in Clinical Oncology Kye Gilder: R code for all figures, figures (PDF), data sets boundary.csv, design.csv, simres.csv
10. Efficient and Effective Review of Clinical Trial Safety Data Using Interactive Graphs and Tables Harry Southworth: Figures were produced using custom libraries such that code cannot be provided. The author may be contacted for particular details.
11. Visualizing Dose-Response when the Signal to Noise Ratio is Low: The Bronchodilatory Response in Chronic Obstructive Pulmonary Disease Michael Looby and Didier Renard: The graphs were produced using proprietary data.
12. Statistical Graphics in Late-Stage Drug Development Julia Wang and Surya Mohanty: to come
13. Graphical Data Exploration in QT Model Building and Cardiovascular Drug Safety Ihab G. Girgis and Surya Mohanty: to come
14. Data Visualization at the Individual Patient Level Matthew Austin and Alicia Zhang: to come
15. Graphics for Meta-Analysis Peter W. Lane, Judith Anzures-Cabrera, Steff Lewis and Jeffrey Tomlinson: Code and figures (zip file)
16. Visualization of QT Data for Thorough QT Study Analysis and Review Christoffer W. Tornøe: R/S-Plus code to run the QT library functions and create the figures, zip file containing code and figures
17. Graphics for Safety Analysis Peter W. Lane and Ohad Amit: SAS, S-Plus, and Genstat code, figures, and data (zip file)
18. Cardiac Safety Richard J. Anziano: to come

Section IV - Operations Marketing and Post-Approval

19. Data Visualization for Clinical Trials Data Management and Operations Ted Snyder: Graphs were produced using Spotfire interactively. Thus, no code available but details of the graph creation are provided here.
20. Post-Approval Uses of Clinical Data, Phase IV Data, and Sales & Marketing Data Visualizations Sam Weerahandi, Birol Emir and Ed Whalen: to come
21. Using Exploratory Visualization in the Analysis of Medical Product Safety in Observational Healthcare Data Patrick Ryan: Graphs were produced using Spotfire interactively. Thus, no code available but details of the graph creation are provided here.