### Overview

These graphs represent some of the displays I have used in my work as a statistical reviewer for FDA. They have benefited from the input of many individuals, in particular Ana Szarfman and Norman Stockbridge of FDA, and Dan Carr of George Mason University. The present work would have been impossible (or at least really, really, hard) without R and the great work done by the R community.

This page provides links to graphical displays for visualizing data from clinical trials. Each page allows the user to either enter their own data or use the provided sample data, to produce a graph. The output from R script is provided, as is the R script used to produce the graph. It is my hope that these scripts will be used by others to learn about R and produce useful visual displays. Because intermediate files are stored on a remote server, I cannot guarantee the privacy of any data entered into the forms.

### Background

The analysis of a clinical trial can be thought of as the answering of a series of questions about the design of the study and the results of the study. In particular the analysis should answer the following questions:

- Is the design of the study capable of meeting the study objectives?
- Are there any gross data errors?(all graphs)
- What types of subjects were studied, and for how long?(timelines, bubble plot, sample sizes by study )
- What happened to the subjects during the course of the study?
- How did the subjects respond to what happened?

### Why R?

R has a comprehensive graphics system, a comprehensive collection of statistical methods, is available for virtually all computer systems, is widely used, and is free.

Technologies used in constructing this web site include Django, Python, R, and Cairo.

R packages used include Cairo, Gplots, Hmisc, MASS, Rcolorbrewer, and treemap

References