Background

Background

This tool provides a concise summary of every variable in a data frame and includes interactive features such as real-time filters, grouping, and highlighting. The R interface allows the analyst to interactively explore datasets within the typical analysis workflow and working environment as shown in the screenshot below and more details are available in the associated manuscript.

While the codebook works any rectangular data set from any data domain, the tool was developed to aid in the exploration and monitoring of clinical trial data. Trials requires vigorous monitoring and exploration of the incoming data. These technical tasks are imperative for ensuring data quality and proper interpretation of study results, but are often time-consuming and awkward using standard static data summaries. The interactive codebook was designed to streamline the process.

The interactive codebook builds upon the existing use of statistical graphics and data visualization in clinical trials by creating a simple interactive framework for exploring data. In particular, codebook takes inspiration from Frank Harrell's excellent describe method from the hmisc R package, as well as previous work in SAS (Calatroni, 2007 and Rosenbalm, 2017) to create concise summaries of every variable in a dataset with minimal user configuration. Like its static codebook predecessors, the web-codebook includes paneled displays, comprehensive data listings, and charts for each variable type, but it expands on these tools by providing interactivity via dynamic filters, collapsible/expandable sections, across-chart data linking, and customizable controls. The resulting tool is well suited for use in many aspects of clinical trial research, including data exploration, anomaly detection, key end point and safety monitoring surveillance.