For each sleep metric, how one night relates to the next night (calendar-adjacent nights only).
Single-subject & observational — Spearman correlations, descriptive not causal.
Each metric vs itself the next night. Positive = a high night tends to repeat (persistence); negative = a high night is followed by a low one (rebound). ✱ = p<0.05.
% change in the next night's metric after a top-third night vs a bottom-third night. Negative = rebound (body corrects downward). ✱ = p<0.05.
Spearman rho. Green = the two move together, red = they move oppositely. Bold + outline = survives multiple-comparison (FDR) correction; dim = not significant (p≥0.05). Hover a cell for details.
Daily event count from primary calendar — counts only, no titles or details. Hover the heatmap above to see steps + meetings together.
Comparing outcomes after high vs low exposure days, controlling for confounders. Effect = difference in means; p-value approximated via permutation test.
| Cause | Effect | High Days (mean) | Low Days (mean) | Difference | Partial r | Confidence |
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Calculating prediction model...
Simple correlations without controlling for confounders. Use causal analysis above for better inference.
| Factor | → Sleep (next day) | → Sleep (+2 days) | → HRV (next day) | → HRV (+2 days) | → Resting HR (next day) |
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How today's activity patterns affect health metrics 1-3 days later.
| Factor | +1 Day Battery | +2 Day Battery | +3 Day Battery | Best Lag |
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Pearson correlation coefficients. Green = positive correlation, Red = negative correlation.
| Metric | Mean | Median | Std Dev | Min | Max | Range |
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The average shape of your day — each metric averaged by hour-of-day across the window set above (widen to 90d / All for stable patterns), so the daily rhythm shows through instead of one day's noise. Combined view shades the hour's min–max range; Weekday vs Weekend overlays the two day types.