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>
69 lines
2.9 KiB
Plaintext
69 lines
2.9 KiB
Plaintext
==============================================================================
|
|
VARIATION: right_only_d0_5
|
|
==============================================================================
|
|
model: behavior ~ stim + day + stim:day + (1|rat) (behavior = success COUNT)
|
|
day = training day within window (0 = first analyzed day)
|
|
treatment (stim=1): Electrode-Box-B2, Right-Electrode
|
|
control (stim=0): Electrode-Box-A2
|
|
N = 7 rats, 42 sessions raw day coverage: treat 0..5, control 0..5
|
|
(equal day coverage over this window)
|
|
|
|
==============================================================================
|
|
FULL MODEL SUMMARY -- fitlme
|
|
==============================================================================
|
|
|
|
Linear mixed-effects model fit by ML
|
|
|
|
Model information:
|
|
Number of observations 42
|
|
Fixed effects coefficients 4
|
|
Random effects coefficients 7
|
|
Covariance parameters 2
|
|
|
|
Formula:
|
|
behavior ~ 1 + day*stim + (1 | rat)
|
|
|
|
Model fit statistics:
|
|
AIC BIC LogLikelihood Deviance
|
|
331.16 341.59 -159.58 319.16
|
|
|
|
Fixed effects coefficients (95% CIs):
|
|
Name Estimate SE tStat DF pValue
|
|
{'(Intercept)'} 12.524 5.1493 2.4321 38 0.019831
|
|
{'day' } 9.8571 1.3751 7.1681 38 1.4583e-08
|
|
{'stim' } -4.9762 6.8119 -0.73051 38 0.46956
|
|
{'day:stim' } 5.3071 1.8191 2.9174 38 0.0058973
|
|
|
|
|
|
Lower Upper
|
|
2.0996 22.948
|
|
7.0733 12.641
|
|
-18.766 8.8138
|
|
1.6245 8.9898
|
|
|
|
Random effects covariance parameters (95% CIs):
|
|
Group: rat (7 Levels)
|
|
Name1 Name2 Type Estimate
|
|
{'(Intercept)'} {'(Intercept)'} {'std'} 5.2482
|
|
|
|
|
|
Lower Upper
|
|
2.2427 12.282
|
|
|
|
Group: Error
|
|
Name Estimate Lower Upper
|
|
{'Res Std'} 9.9638 7.8829 12.594
|
|
|
|
|
|
effect t(df) / F(df1) p (resid) Satterthwaite: p (df)
|
|
----------------------------------------------------------------------------
|
|
stim x day (interaction) t(38)= 2.92 F(1)= 8.511 p=0.005897 p=0.006128 (df=35)
|
|
day (learning) t(38)= 7.17 F(1)= 51.382 p=1.458e-08 p=2.321e-08 (df=35)
|
|
stim (main, window start) t(38)= -0.73 F(1)= 0.534 p=0.4696 p=0.4735 (df=20)
|
|
interaction 95% CI: [+1.62, +8.99]
|
|
HONEST LME (per-animal random slope, day|rat): interaction F(1,7.0)=3.94, p=0.08763
|
|
(Satterthwaite DF ~= residual on this random-intercept model; the random-slope
|
|
model above is the honest learning-rate test -- DF collapses toward the animal count.)
|
|
INTERPRETATION: stim x day interaction SIGNIFICANT positive -- treatment improves FASTER (benefit accumulates) (p=0.005897, slope diff=+5.31)
|
|
Paper (N=24): interaction t(227)=2.68, F(1)=7.12, p=0.008.
|