|Title||Conducting High-Value Secondary Dataset Analysis: An Introductory Guide and Resources|
|Publication Type||Journal Article|
|Year of Publication||2011|
|Authors||Ayanian, JZ, Covinsky, KE, Landon, BE, McCarthy, E, Wee, CC, Steinman, MA|
|Journal||Journal of General Internal Medicine|
|Keywords||Datasets, Meta-analyses, Survey Methodology|
Secondary analyses of large datasets provide a mechanism for researchers to address high impact questions that would otherwise be prohibitively expensive and time-consuming to study. This paper presents a guide to assist investigators interested in conducting secondary data analysis, including advice on the process of successful secondary data analysis as well as a brief summary of high-value datasets and online resources for researchers, including the SGIM dataset compendium (www.sgim.org/go/datasets). The same basic research principles that apply to primary data analysis apply to secondary data analysis, including the development of a clear and clinically relevant research question, study sample, appropriate measures, and a thoughtful analytic approach. A real-world case description illustrates key steps: (1) define your research topic and question; (2) select a dataset; (3) get to know your dataset; and (4) structure your analysis and presentation of findings in a way that is clinically meaningful. Secondary dataset analysis is a well-established methodology. Secondary analysis is particularly valuable for junior investigators, who have limited time and resources to demonstrate expertise and productivity.
|PubMed Central ID||PMC3138974|