Speaker
Description
In social science research, datasets are often confidential, requiring analyses to be conducted in secure remote access environments. One such environment is FIONA, which provides researchers with access to sensitive, unit-level Finnish register data alongside standard statistical software, including R. We use FIONA to analyse extensive register data on Finnish teenagers and young adults, with a substantive focus on deaths of despair, including suicide, overdoses, and violence.
R is a natural choice due to its open-source ecosystem and flexibility, which support tool development within FIONA despite the constraints of a closed environment. However, constraints such as limited computational resources, restrict model complexity and require careful workflow planning. While basic models can be fitted in reasonable time, more demanding approaches can become infeasible. Memory constraints further necessitate careful handling of large datasets and intermediate outputs. Additionally, fixed CRAN snapshots may limit access to recent or non-CRAN packages, requiring alternative tools.
We discuss practical strategies for addressing these constraints, including staged model development starting from simple specifications, careful management of intermediate results, and theory-driven variable selection to reduce unnecessary computation. We also describe the use of parallel computing tools to speed up analyses where feasible.
Reproducibility and openness raise important challenges in secure environments. Although the data cannot be shared, we aim to publish full analysis code, model specifications, and detailed data descriptions.
Overall, the presentation provides concrete recommendations for conducting reproducible and efficient R-based research in secure environments, while highlighting limitations that should inform the future development of such infrastructures.
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| Keywords: Please list up to 5 keywords to help us find the right session for your contribution. | Remote access environments, R workflows, register data, computational restraints, reproducible research |
|---|---|
| Virtual Option | This submission is for onsite presentation only |
| Video Recording | Video sharing is fine |
| The author(s) agree(s) to take responsibility and be accountable for the contents of the submission and is/are authorized to present it. | Confirm |