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LOG-DAY MODEL + COHEN'S f + POWER -- right_only_d0_10   [metric: success RATE]
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model: behavior ~ stim + log(day) + stim:log(day) + (1|rat)   (behavior = success RATE)
log(day) uses 1-indexed training day (our day 0 = paper "Day 1")
observed groups: stim n=4, control n=3   nrep=120, alpha=0.05

--- fitted on real data ---
stim x log(day) interaction: F(1,68)=13.480  p(resid)=0.0004756  p(Satt)=0.0004808 (df=67)
  honest per-animal random slope (log-day): F(1,62.4)=13.42  p=0.0005158
Cohen's f (interaction, partial eta^2=0.033) = 0.185  (small-medium; f: .10 small, .25 medium, .40 large)

--- power simulation (log-day ground truth: stim:logday=+0.095, ratSD=0.04259, resSD=0.07524) ---

 true stim:log(day) = +0.095 (100% of observed)
  N/group  | per-animal power | LME power
  ------------------------------------------
  3        |  0.63            |  0.95  <- observed
  5        |  0.99            |  1.00
  8        |  1.00            |  1.00
  12       |  1.00            |  1.00
  16       |  1.00            |  1.00
  24       |  1.00            |  1.00

 true stim:log(day) = +0.0475 (50% of observed)
  N/group  | per-animal power | LME power
  ------------------------------------------
  3        |  0.23            |  0.42  <- observed
  5        |  0.55            |  0.66
  8        |  0.78            |  0.82
  12       |  0.96            |  0.97
  16       |  0.98            |  1.00
  24       |  0.99            |  1.00

Read per-animal as the honest power; LME matches the paper's power code (optimistic).
