🔬Research & N-of-1

Rigorous experimental design for applied and academic research.

Decision Process supports behavioral, social, and applied researchers who need Bayesian inference, clean randomization, and structured data collection — without standing up a custom analysis pipeline for every study.

Experiment Templates

Ready-to-run experiments

Work Block Length (N-of-1)

90-minute deep work blocks produce higher daily output than 50-minute blocks.

Conditions

  • 50 min blocks (control)
  • 90 min blocks

Metrics

  • Self-Report Rating (1–10)
  • Reaction Time (ms)
  • Protocol Adherence (%)
DayRun experiment →

Exercise Timing (N-of-1)

Morning exercise improves same-day focus and mood more than evening exercise.

Conditions

  • Morning (6–9 AM) (control)
  • Evening (5–8 PM)

Metrics

  • Self-Report Rating (1–10)
  • Reaction Time (ms)
  • Protocol Adherence (%)
DayRun experiment →

Sleep Duration Target (N-of-1)

Targeting 8 hours of sleep produces meaningfully better next-day performance than 7 hours.

Conditions

  • 7h target (control)
  • 8h target

Metrics

  • Self-Report Rating (1–10)
  • Reaction Time (ms)
  • Protocol Adherence (%)
DayRun experiment →

Caffeine Delay Protocol (N-of-1)

Delaying first caffeine to 90–120 minutes after waking reduces afternoon energy crash.

Conditions

  • Immediate (0–30 min) (control)
  • Delayed (90–120 min)

Metrics

  • Self-Report Rating (1–10)
  • Protocol Adherence (%)
DayRun experiment →

Worked Example

Spaced vs. massed study sessions across 84 participants

A cognitive psychology lab assigns participants to either a massed study session (2-hour block) or a spaced condition (4 × 30-minute sessions over one week) for the same learning material. 42 participants per arm. Retention measured via test at 30 days.

Results: retention_score (%)

Massed practice (control)

mean: 58.3%

95% CI: 53.1–63.5

Spaced repetition

mean: 74.7%

95% CI: 69.8–79.6

P(better) = 99%

Spaced repetition produces a +16.4 percentage point improvement in 30-day retention (d = +0.91, large effect) at 99% posterior probability. This replicates the well-known spacing effect with high confidence in this sample. Results are ready for pre-registration and publication.

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