analysis(matlab): rate + count outputs, variation batch 1
Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
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@@ -1,11 +1,11 @@
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==============================================================================
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POWER SIMULATION -- boxa_a2_d6_10
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POWER SIMULATION -- boxa_a2_d6_10 [metric: # successes (count)]
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==============================================================================
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model: behavior ~ stim + day + stim:day + (1|rat) (success COUNT; day within-window)
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model: behavior ~ stim + day + stim:day + (1|rat) (behavior = # successes (count); day within-window)
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observed groups: stim n=3, control n=3 nrep=120, alpha=0.05
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ground truth: stim:day=+1.00/day, rat SD=6.34, residual SD=8.21, days=5
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ground truth: stim:day=+1/day, rat SD=6.344, residual SD=8.208, days=5
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true stim:day interaction = +1.00 (100% of observed)
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true stim:day interaction = +1 (100% of observed)
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N/group | per-animal power | LME power
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------------------------------------------
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3 | 0.03 | 0.05 <- observed
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@@ -15,7 +15,7 @@ ground truth: stim:day=+1.00/day, rat SD=6.34, residual SD=8.21, days=5
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16 | 0.12 | 0.14
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24 | 0.27 | 0.32
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true stim:day interaction = +0.50 (50% of observed)
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true stim:day interaction = +0.5 (50% of observed)
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N/group | per-animal power | LME power
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------------------------------------------
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3 | 0.05 | 0.09 <- observed
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@@ -25,5 +25,4 @@ ground truth: stim:day=+1.00/day, rat SD=6.34, residual SD=8.21, days=5
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16 | 0.08 | 0.11
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24 | 0.12 | 0.12
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Read the per-animal column as the honest power. At the observed N this study
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is typically underpowered; per-animal power reaches ~0.8 only at larger N.
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Read the per-animal column as the honest power; LME is optimistic (obs-level DF).
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