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 -- unmerge_d0_10
|
|
==============================================================================
|
|
model: behavior ~ stim + day + stim:day + (1|rat) (success COUNT; day within-window)
|
|
observed groups: stim n=3, control n=3 nrep=120, alpha=0.05
|
|
ground truth: stim:day=+1.56/day, rat SD=5.35, residual SD=12.51, days=11
|
|
|
|
true stim:day interaction = +1.56 (100% of observed)
|
|
N/group | per-animal power | LME power
|
|
------------------------------------------
|
|
3 | 0.15 | 0.31 <- observed
|
|
5 | 0.44 | 0.56
|
|
8 | 0.59 | 0.66
|
|
12 | 0.88 | 0.90
|
|
16 | 0.93 | 0.95
|
|
24 | 0.99 | 1.00
|
|
|
|
true stim:day interaction = +0.78 (50% of observed)
|
|
N/group | per-animal power | LME power
|
|
------------------------------------------
|
|
3 | 0.11 | 0.11 <- observed
|
|
5 | 0.09 | 0.13
|
|
8 | 0.22 | 0.23
|
|
12 | 0.32 | 0.32
|
|
16 | 0.47 | 0.47
|
|
24 | 0.63 | 0.60
|
|
|
|
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.
|