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Research Data Merger
Merge messy research files without hiding the decisions
2 followers
Merge messy research files without hiding the decisions
2 followers
Merge participant, survey, roster, and longitudinal study files by ID. Review mismatches, duplicates, repeated measurements, and incomplete responses before exporting a documented, analysis-ready dataset. Everything stays local.
Hi, I built Research Data Merger for a problem that looks simple until you actually have to deal with it.
A study may include a participant roster, a baseline survey, Week 4 and Week 8 exports, and another file containing demographics. The IDs almost match. Some columns repeat because they are new measurements. One participant appears twice. Another only exists in one source.
A normal merge can produce a file very quickly, but it can also hide a lot of those decisions.
Research Data Merger is designed to keep that preparation step visible. You choose the base table, review ID mismatches and duplicates, preserve repeated measurements, and optionally create filtered, de-identified, or reshaped copies afterward.
There is no research-data upload step in Research Data Merger. Your files are opened, processed, and exported locally on your Mac. They are not sent to IMPLEMON, a cloud service, or an AI model.
I’m keeping the tool intentionally focused on research-data preparation rather than analysis. I’d be especially interested to see how it fits real longitudinal and survey workflows.