Carrying out streamlined routine data analyses with reports for observational studies: introduction to a series of generic SAS ® macros [version 2; peer review: 2 approved] - Liu, Yuan; Nickleach, Dana C; Zhang, Chao; Switchenko, Jeffrey M; Kowalski, Jeanne (F1000 research, 2018)
For a typical medical research project based on observational data, sequential routine analyses are often essential to comprehend the data on hand and to draw valid conclusions.  However, generating reports in SAS ® for routine analyses can be a time-consuming and tedious process, especially when dealing with large databases with a massive number of variables in an iterative and collaborative research environment. In this work, we present a general workflow of research based on an observational database and a series of SAS ® macros that fits this framework, which covers a streamlined data analyses and produces journal-quality summary tables. The system is generic enough to fit a variety of research projects and enables researchers to build a highly organized and concise coding for quick updates as research evolves. The result reports promote communication in collaborations and will escort the research with ease and efficiency.