Literature DB >> 31231506

Carrying out streamlined routine data analyses with reports for observational studies: introduction to a series of generic SAS ® macros.

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


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