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LOG-DAY MODEL + COHEN'S f + POWER -- right_only_d6_10
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model: behavior ~ stim + log(day) + stim:log(day) + (1|rat)   (success COUNT)
log(day) uses 1-indexed training day (our day 0 = paper "Day 1")
observed groups: stim n=4, control n=2   nrep=120, alpha=0.05

--- fitted on real data ---
stim x log(day) interaction: F(1,26)=1.327  p(resid)=0.2599  p(Satt)=0.2608 (df=24)
  honest per-animal random slope (log-day): F(1,6.0)=0.96  p=0.3641
Cohen's f (interaction, partial eta^2=0.021) = 0.145  (small-medium; f: .10 small, .25 medium, .40 large)

--- power simulation (log-day ground truth: stim:logday=+23.04, ratSD=5.69, resSD=8.25) ---

 true stim:log(day) = +23.04 (100% of observed)
  N/group  | per-animal power | LME power
  ------------------------------------------
  3        |  0.07            |  0.28
  5        |  0.28            |  0.38
  8        |  0.44            |  0.50
  12       |  0.61            |  0.61
  16       |  0.76            |  0.78
  24       |  0.97            |  0.97

 true stim:log(day) = +11.52 (50% of observed)
  N/group  | per-animal power | LME power
  ------------------------------------------
  3        |  0.07            |  0.13
  5        |  0.11            |  0.14
  8        |  0.10            |  0.15
  12       |  0.19            |  0.23
  16       |  0.25            |  0.25
  24       |  0.45            |  0.52

Read the per-animal column as the honest power; the LME column matches the
paper's power code (anova interaction p, observation-level DF) and is optimistic.