Experiments DB Dev
bb5e2d88c0
Add variation_power.m (self-contained Monte-Carlo power for the paper's stim x day interaction, using each folder's own data as ground truth; scores per-animal cluster-honest power + LME power across N=[3..24] and effect multipliers 1/0.5) and make_variation_power.m, which drops powersim.m into every variations/<name>/ folder and runs it, writing power_result.txt beside the existing data.csv/analyze.m/result.txt. Named powersim (not power) to avoid shadowing the MATLAB builtin. All 28 folders processed. Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
30 lines
1.3 KiB
Plaintext
30 lines
1.3 KiB
Plaintext
==============================================================================
|
|
POWER SIMULATION -- naive_a2_d0_13
|
|
==============================================================================
|
|
model: behavior ~ stim + day + stim:day + (1|rat) (success COUNT; day within-window)
|
|
observed groups: stim n=3, control n=7 nrep=120, alpha=0.05
|
|
ground truth: stim:day=+1.61/day, rat SD=8.46, residual SD=15.26, days=14
|
|
|
|
true stim:day interaction = +1.61 (100% of observed)
|
|
N/group | per-animal power | LME power
|
|
------------------------------------------
|
|
3 | 0.22 | 0.53 <- observed
|
|
5 | 0.53 | 0.68
|
|
8 | 0.83 | 0.88
|
|
12 | 0.97 | 1.00
|
|
16 | 0.98 | 0.98
|
|
24 | 1.00 | 1.00
|
|
|
|
true stim:day interaction = +0.81 (50% of observed)
|
|
N/group | per-animal power | LME power
|
|
------------------------------------------
|
|
3 | 0.12 | 0.21 <- observed
|
|
5 | 0.21 | 0.21
|
|
8 | 0.42 | 0.42
|
|
12 | 0.50 | 0.53
|
|
16 | 0.64 | 0.72
|
|
24 | 0.78 | 0.75
|
|
|
|
Read the per-animal column as the honest power. At the observed N this study
|
|
is typically underpowered; per-animal power reaches ~0.8 only at larger N.
|