| Literature DB >> 31231506 |
Yuan Liu1,2, Dana C Nickleach2, Chao Zhang2, Jeffrey M Switchenko1,2, Jeanne Kowalski1,2,3.
Abstract
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.Entities:
Keywords: Good-Research-Practice; SAS® macros; collaborative; observational studies; reporting; streamlined data process
Mesh:
Year: 2018 PMID: 31231506 PMCID: PMC6567291 DOI: 10.12688/f1000research.16866.2
Source DB: PubMed Journal: F1000Res ISSN: 2046-1402