Experiments DB Dev
9af33e747e
Add make_matched_effort.m: pick the current-study day cutoff whose per-animal cumulative attempts best match the previous (_f) study's full-span total (~405 attempts/animal -> current days 0-3), then fit the paper LME on both. Two variation folders (data.csv + analyze.m + result.txt): variations/prev_f_full/ b2_f vs a2_f, days 0-9 (24 rats) variations/matched_current_d0_3/ Box-B2 vs Box-A2, 0-3 (6 rats) At matched cumulative effort both show a significant positive stim x day interaction (prev p=0.008 +0.56/day; current-0-3 p=0.004 +10.2/day) -- the tDCS acceleration replicates at equal practice, though the count slopes are not directly comparable across datasets given differing attempts/session. Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
66 lines
2.5 KiB
Plaintext
66 lines
2.5 KiB
Plaintext
==============================================================================
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VARIATION: matched_current_d0_3
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==============================================================================
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model: behavior ~ stim + day + stim:day + (1|rat) (behavior = success COUNT)
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day = training day within window (0 = first analyzed day)
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treatment (stim=1): Electrode-Box-B2
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control (stim=0): Electrode-Box-A2
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N = 6 rats, 24 sessions raw day coverage: treat 0..3, control 0..3
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(equal day coverage over this window)
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==============================================================================
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FULL MODEL SUMMARY -- fitlme
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==============================================================================
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Linear mixed-effects model fit by ML
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Model information:
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Number of observations 24
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Fixed effects coefficients 4
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Random effects coefficients 6
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Covariance parameters 2
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Formula:
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behavior ~ 1 + day*stim + (1 | rat)
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Model fit statistics:
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AIC BIC LogLikelihood Deviance
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185.35 192.42 -86.676 173.35
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Fixed effects coefficients (95% CIs):
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Name Estimate SE tStat DF pValue
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{'(Intercept)'} 16.867 4.4554 3.7856 20 0.0011608
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{'day' } 6.3667 2.2049 2.8875 20 0.0091051
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{'stim' } -8.9667 6.3009 -1.4231 20 0.17013
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{'day:stim' } 10.2 3.1182 3.2711 20 0.0038217
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Lower Upper
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7.5728 26.161
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1.7673 10.966
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-22.11 4.1769
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3.6955 16.705
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Random effects covariance parameters (95% CIs):
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Group: rat (6 Levels)
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Name1 Name2 Type Estimate
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{'(Intercept)'} {'(Intercept)'} {'std'} 2.9163
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Lower Upper
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0.43116 19.725
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Group: Error
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Name Estimate Lower Upper
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{'Res Std'} 8.5397 6.1599 11.839
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effect t (df) F (df1) p
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------------------------------------------------------------------
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stim x day (interaction) t(20)= 3.27 F(1)= 10.700 p=0.003822
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day (learning) t(20)= 2.89 F(1)= 8.337 p=0.009105
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stim (main, window start) t(20)= -1.42 F(1)= 2.025 p=0.1701
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interaction 95% CI: [+3.70, +16.70]
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INTERPRETATION: stim x day interaction SIGNIFICANT positive -- treatment improves FASTER (benefit accumulates) (p=0.003822, slope diff=+10.20)
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Paper (N=24): interaction t(227)=2.68, F(1)=7.12, p=0.008.
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