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: naive_a2_d0_13
|
|
==============================================================================
|
|
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
|
|
control (stim=0): Electrode-Box-A2, Naive
|
|
N = 10 rats, 124 sessions raw day coverage: treat 0..13, control 0..13
|
|
(equal day coverage over this window)
|
|
|
|
==============================================================================
|
|
FULL MODEL SUMMARY -- fitlme
|
|
==============================================================================
|
|
|
|
Linear mixed-effects model fit by ML
|
|
|
|
Model information:
|
|
Number of observations 124
|
|
Fixed effects coefficients 4
|
|
Random effects coefficients 10
|
|
Covariance parameters 2
|
|
|
|
Formula:
|
|
behavior ~ 1 + day*stim + (1 | rat)
|
|
|
|
Model fit statistics:
|
|
AIC BIC LogLikelihood Deviance
|
|
1055.4 1072.3 -521.69 1043.4
|
|
|
|
Fixed effects coefficients (95% CIs):
|
|
Name Estimate SE tStat DF pValue
|
|
{'(Intercept)'} 16.252 4.4327 3.6664 120 0.00036779
|
|
{'day' } 6.4053 0.43948 14.575 120 2.5469e-28
|
|
{'stim' } 11.52 8.023 1.4359 120 0.15363
|
|
{'day:stim' } 1.6137 0.77637 2.0785 120 0.039797
|
|
|
|
|
|
Lower Upper
|
|
7.4757 25.029
|
|
5.5352 7.2755
|
|
-4.3648 27.405
|
|
0.076509 3.1508
|
|
|
|
Random effects covariance parameters (95% CIs):
|
|
Group: rat (10 Levels)
|
|
Name1 Name2 Type Estimate
|
|
{'(Intercept)'} {'(Intercept)'} {'std'} 8.4599
|
|
|
|
|
|
Lower Upper
|
|
4.8243 14.835
|
|
|
|
Group: Error
|
|
Name Estimate Lower Upper
|
|
{'Res Std'} 15.264 13.405 17.381
|
|
|
|
|
|
effect t(df) / F(df1) p (resid) Satterthwaite: p (df)
|
|
----------------------------------------------------------------------------
|
|
stim x day (interaction) t(120)= 2.08 F(1)= 4.320 p=0.0398 p=0.03986 (df=117)
|
|
day (learning) t(120)= 14.57 F(1)=212.424 p=2.547e-28 p=3.246e-28 (df=119)
|
|
stim (main, window start) t(120)= 1.44 F(1)= 2.062 p=0.1536 p=0.1655 (df=21)
|
|
interaction 95% CI: [+0.08, +3.15]
|
|
HONEST LME (per-animal random slope, day|rat): interaction F(1,41.7)=3.81, p=0.05781
|
|
(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=0.0398, slope diff=+1.61)
|
|
Paper (N=24): interaction t(227)=2.68, F(1)=7.12, p=0.008.
|