● raises · ● lowers · more dots = higher confidence
| Factor | Effect | Impact / SD | Strength | r | Conf. |
|---|
How your habits cluster, and how much of the day‑to‑day variation a few patterns capture.
Effect: whether more of this factor tends to raise or lower pain, from a multi‑factor regression (controls for the others).
Impact / SD: pain points (0–10 scale) change for a 1 standard‑deviation change in the factor — a fair way to compare units.
Strength: random‑forest permutation importance — how much the model relies on this factor, capturing non‑linear effects.
r: simple pairwise correlation with pain.
Conf.: our confidence, blending statistical significance, agreement between models, forest importance and how much data you have.
Same‑day analysis misses anything that hits with a delay (post‑exertional crashes, migraine build‑up). A separate pass checks each factor a few days back, after controlling for your own recent trend, so a slow drift isn't mistaken for a driver. A confound note appears when two factors move together closely enough that we can't confidently credit one over the other from observation alone.
Log ~15 days to unlock experiments.
Suggested test levels are capped to general safety limits (e.g. ≤400mg caffeine/day, ≥4h sleep/night) — not personalized medical advice. Check with a clinician before testing anything that feels wrong for you.
logged predicted next — tap a day to log or remove