Abstract: A frequently expressed barrier to the transition from SAS to R at our institution is the challenge in generating “quick and dirty” output that combines text and graphical summaries of data for offline viewing or sharing with investigators. Depending on a person’s prior training and programming style, a full markdown approach to produce this integrated summary often requires significant reprogramming, particularly when the project involves multiple programmers or complex data manipulation. The philosophy behind an approach entitled “object-oriented markdown” will be presented and illustrated using a series of research projects utilizing the RJafroc package. The presentation will illustrate how data management and analysis standards can provide a framework that enables collaboration amongst statisticians on the project and ease of integration of final statistical results into a markdown document. By utilizing a markdown file only as a means to print stored R objects, one is able to rapidly summarize and interpret statistical output while maintaining efficient programming styles. Keywords: Reproducible research, statistical output, data analysis pipeline
