Liberal Arts and Sciences
Ekvall Lab
Led by Karl Oskar Ekvall · Statistics
What we study
The Ekvall Lab studies statistical methods for complex data, like mixed models and high-dimensional problems. They develop theory, algorithms, and software for reliable inference in fields like biomedicine and economics.
What working here is like
- Computational
- Reading, writing & theory
- No organisms (data only)
- Coding required
- Papers
- 5
Recent papers, explained
- Universal Inference for Variance Components
2026 · Stat
Creates new statistical methods for analyzing variance components near boundaries.
- Likelihood‐Based Inference With Separable Correlation Matrices
2026 · Stat
Develops faster methods for statistical inference with separable correlation matrices.
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- Validation and comparison of two prearrest prediction scores for in-hospital cardiac arrest survival
2026 · Resuscitation Plus
Validates and compares two scores to predict survival after in-hospital cardiac arrest.
- Fast and reliable confidence intervals for a variance component
2025 · Biometrika
Builds reliable confidence intervals for variance components in small samples.
- Uniform inference in linear mixed models
2025 · Biometrika
Provides better statistical methods for analyzing random effects in mixed models.
Plain-language summaries are AI-written and reviewed by us; check the paper for details.
How to reach out
Karl Oskar Ekvall hasn't set up this page yet. Their UF Scholars profile lists their publications.