@article {8744,
	title = {Conducting High-Value Secondary Dataset Analysis: An Introductory Guide and Resources},
	journal = {Journal of General Internal Medicine},
	volume = {26},
	year = {2011},
	pages = {920-929},
	abstract = {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.},
	keywords = {Datasets, Meta-analyses, Survey Methodology},
	issn = {0884-8734},
	doi = {10.1007/s11606-010-1621-5},
	author = {John Z. Ayanian and Kenneth E Covinsky and Landon, Bruce E. and Ellen P McCarthy and Wee, Christina C. and Michael A Steinman}
}
