Analysis of data dictionary formats of HIV clinical trials.
Craig S MayerNick WilliamsVojtech HuserPublished in: PloS one (2020)
We saw features of data dictionaries that made them difficult to use and understand. This included multiple data dictionary files or non-machine-readable documents, data elements included in data but not in the dictionary or missing data types or descriptions. Building on experience with aggregating data elements across a large set of studies, we created a set of recommendations (called CONSIDER statement) that can guide optimal data sharing of future studies.