Secondary Analysis of Quantitative Data

Abstract

Secondary analysis is the analysis of data that have originally been collected either for a different purpose or by a different researcher or organisation. Because of the cost and complexity of primary data collection, and because of the opportunities offered by “found” data not originally collected for research purposes (e.g., administrative records, Internet use), most data analysis except for small-scale or experimental studies and qualitative work is now secondary in character. This is a relatively recent development since good data archives only began to be established since the 1970s. Because of the ways in which it can be more readily standardised, anonymised, and curated, secondary analysis of quantitative data is more common than for qualitative studies. Secondary analysis promotes transparency, reproducibility, and replication in research and facilitates the cumulative growth of knowledge. Because of this research funders typically require requests for primary data collection to demonstrate that secondary analysis of existing data is not a feasible alternative, and require the creators of new data to document it adequately and submit it to a relevant archive for curation.

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