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analysis(matlab): rate + count outputs, variation batch 2

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Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
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Experiments DB Dev
2026-07-24 02:32:52 -04:00
parent 0a438a4649
commit 6ba21a1a35
72 changed files with 1874 additions and 896 deletions
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analysis/matlab/variations/naive_a2_d6_10/logpower_result.txt
+4 -5
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@@ -1,7 +1,7 @@
==============================================================================
LOG-DAY MODEL + COHEN'S f + POWER -- naive_a2_d6_10
LOG-DAY MODEL + COHEN'S f + POWER -- naive_a2_d6_10 [metric: # successes (count)]
==============================================================================
model: behavior ~ stim + log(day) + stim:log(day) + (1|rat) (success COUNT)
model: behavior ~ stim + log(day) + stim:log(day) + (1|rat) (behavior = # successes (count))
log(day) uses 1-indexed training day (our day 0 = paper "Day 1")
observed groups: stim n=3, control n=6 nrep=120, alpha=0.05
@@ -22,7 +22,7 @@ Cohen's f (interaction, partial eta^2=0.006) = 0.076 (small; f: .10 small, .25
16 | 0.34 | 0.36
24 | 0.51 | 0.53
true stim:log(day) = -8.46 (50% of observed)
true stim:log(day) = -8.464 (50% of observed)
N/group | per-animal power | LME power
------------------------------------------
3 | 0.03 | 0.07 <- observed
@@ -32,5 +32,4 @@ Cohen's f (interaction, partial eta^2=0.006) = 0.076 (small; f: .10 small, .25
16 | 0.11 | 0.12
24 | 0.13 | 0.14
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.
Read per-animal as the honest power; LME matches the paper's power code (optimistic).