Open problems
Five problems we want help with.
Each is concrete enough to start on, with data or code that already exists. Pick one and tell us.
P1. Identifying personal parameters from three to five visits
Cohorts measure blood every two to four years. What can be identified about a person's own parameters (position, rate of drift, sensitivity) from so few points, and how should shrinkage toward the population be designed so it is honest about what one person's data can say?
P2. Separating ageing, cohort and survival
Cross-sectional age gradients mix true within-person change with birth-cohort differences and the selective survival of healthier people. Of 123 markers, 110 drift with age cross-sectionally. How much of that is real movement?
P3. Informative sampling in clinical lab data
Clinical labs are dense but ordered when something is wrong. Joint models of when a test is taken and what it shows are needed before routine health-system data can be used.
P4. Resilience as a measurable quantity
Complex-systems theory predicts rising variance and autocorrelation as a regulated system loses stability. Which estimators survive sparse, noisy, irregular observation?
P5. The value of a measurement
Which test, at which age, most reduces uncertainty about a person's future? Expected information gain per dollar turns the landscape into a decision tool.