Experiments DB Dev
8a18c894dd
Every fitlme-based report (lme_*, paper_*, phase_*, and the variations' analyze.m) now shows, per effect: residual-DF p, Satterthwaite-DF p, and -- for the interaction -- an HONEST test from a per-animal random-SLOPE model (day|rat), whose Satterthwaite DF collapses toward the animal count. New: tdcs_random_slope_interaction.m (shared helper). Wired into tdcs_lme, tdcs_paper_lme, tdcs_phase_lme, variation_analyze; SUMMARY.csv gains interaction_p_satt / interaction_p_rs. Regenerated all results/, variations/, matched-effort outputs. Key point this surfaces: Satterthwaite ~= residual on the random-INTERCEPT model (the slope's error is at session level), so it does NOT fix pseudoreplication; the random-slope model does. Effect: full-range mergeA2 interaction 0.009 -> 0.75 (collapses); unmerge_d0_5 0.015 -> 0.13 (n.s.); the pooled-control early windows survive honestly (naive_a2_d0_5 0.001 -> 0.028; naive_boxa_d0_5 0.003 -> 0.036). Suite 42/42. Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
78 lines
3.4 KiB
Plaintext
78 lines
3.4 KiB
Plaintext
==============================================================================
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PAPER LME REPLICATION -- mergeA2 (full range)
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==============================================================================
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model: behavior ~ stim + day + stim:day + (1|rat) [stim: Electrode-Box-B2=1 vs Electrode-Box-A2=0]
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behavior = successful reaches (COUNT per session)
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N = 8 rats, 109 sessions (day raw; day 0 = paper "Day 1")
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day coverage: stim(B2) 0..22, control(A2) 0..14
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** WARNING: unequal day coverage -- the full-range stim:day interaction
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extrapolates the control group's line and is CONFOUNDED here (the paper's
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groups had equal coverage). See the _d0_13 fair-window and phased analyses. **
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==============================================================================
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FULL MODEL SUMMARY -- fitlme: behavior ~ stim + day + stim:day + (1|rat)
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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 109
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Fixed effects coefficients 4
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Random effects coefficients 8
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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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962.68 978.83 -475.34 950.68
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Fixed effects coefficients (95% CIs):
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Name Estimate SE tStat DF pValue
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{'(Intercept)'} 20.701 4.9127 4.2138 105 5.3256e-05
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{'day' } 6.8599 0.69872 9.8178 105 1.5726e-16
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{'stim' } 22.092 6.4372 3.4319 105 0.00085848
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{'day:stim' } -2.1793 0.81821 -2.6635 105 0.0089525
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Lower Upper
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10.96 30.442
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5.4745 8.2453
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9.3279 34.855
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-3.8016 -0.55692
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Random effects covariance parameters (95% CIs):
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Group: rat (8 Levels)
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Name1 Name2 Type Estimate
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{'(Intercept)'} {'(Intercept)'} {'std'} 2.1043e-15
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Lower Upper
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NaN NaN
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Group: Error
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Name Estimate Lower Upper
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{'Res Std'} 18.954 16.597 21.644
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effect t(df) / F(df1) p (resid) Satterthwaite: p (df)
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----------------------------------------------------------------------------
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stim x day (interaction) t(105)= -2.66 F(1)= 7.094 p=0.008953 p=0.008906 (df=109)
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day (learning) t(105)= 9.82 F(1)= 96.388 p=1.573e-16 p=1.113e-16 (df=109)
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stim (main, Day 1) t(105)= 3.43 F(1)= 11.778 p=0.0008585 p=0.000848 (df=109)
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interaction 95% CI: [-3.80, -0.56]
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HONEST LME -- per-rat random slope (day|rat): interaction F(1,9.7)=0.11, p=0.746
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Satterthwaite DF on the random-INTERCEPT model above stays ~= residual (the
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slope's error is at session level), so it does NOT fix pseudoreplication. A per-animal
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random slope collapses the interaction DF toward the animal count -- the honest test.
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INTERPRETATION
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- stim x day interaction: SIGNIFICANT (p=0.0090, slope diff=-2.18) -> tDCS (Box-B2) improves SLOWER -- groups converge.
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- stim main effect on Day 1 (our day 0): SIGNIFICANT (p=0.0009) -> groups already DIFFER on Day 1.
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Paper (N=24): interaction t(227)=2.68, F(1)=7.12, p=0.008; day t(227)=9.64,
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F(1)=267.64, p=1.2e-18; stim t(227)=0.23, F(1)=0.053, p=0.81.
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