analysis(matlab): Box-A pooling variations (b2 vs a2+a, b2+a vs a2)

Add make_boxa_variations.m producing 6 variation folders (data.csv + analyze.m + result.txt) for the paper LME over windows 0-5, 6-10, 0-10: boxa_a2 B2 vs A2 + Box-A (b2 vs a2+a) boxa_b2 B2 + Box-A vs A2 (b2+a vs a2) plus variations/boxa_summary.csv (residual / Satterthwaite / random-slope interaction p). Early window (0-5) is obs-level significant (res p~0.03-0.04) but n.s. under the honest random-slope test (rs p~0.13); later windows n.s. Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
2026-07-23 13:39:01 -04:00
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+==============================================================================
+VARIATION: boxa_a2_d0_10
+==============================================================================
+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-A, Electrode-Box-A2
+N = 7 rats, 72 sessions   raw day coverage: treat 0..10, control 0..10
+(equal day coverage over this window)
+
+==============================================================================
+FULL MODEL SUMMARY -- fitlme
+==============================================================================
+
+Linear mixed-effects model fit by ML
+
+Model information:
+    Number of observations              72
+    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
+    590.8    604.46    -289.4           578.8   
+
+Fixed effects coefficients (95% CIs):
+    Name                   Estimate    SE         tStat     DF    pValue    
+    {'(Intercept)'}        15.599       3.8531    4.0485    68    0.00013444
+    {'day'        }        8.3258      0.69175    12.036    68    1.6397e-18
+    {'stim'       }        6.7494       5.8389    1.1559    68       0.25175
+    {'day:stim'   }        1.1985       1.0141    1.1818    68        0.2414
+
+
+    Lower       Upper 
+      7.9104    23.288
+      6.9454    9.7061
+     -4.9019    18.401
+    -0.82514    3.2221
+
+Random effects covariance parameters (95% CIs):
+Group: rat (7 Levels)
+    Name1                  Name2                  Type           Estimate
+    {'(Intercept)'}        {'(Intercept)'}        {'std'}        0       
+
+
+    Lower    Upper
+    NaN      NaN  
+
+Group: Error
+    Name               Estimate    Lower     Upper 
+    {'Res Std'}        13.471      11.441    15.861
+
+
+effect                     t(df) / F(df1)     p (resid)    Satterthwaite: p (df)
+----------------------------------------------------------------------------
+stim x day (interaction)   t(68)=  1.18 F(1)=  1.397  p=0.2414    p=0.2412 (df=72)
+day (learning)             t(68)= 12.04 F(1)=144.862  p=1.64e-18    p=6.575e-19 (df=72)
+stim (main, window start)  t(68)=  1.16 F(1)=  1.336  p=0.2517    p=0.2515 (df=72)
+interaction 95% CI: [-0.83, +3.22]
+HONEST LME (per-animal random slope, day|rat): interaction F(1,14.0)=0.68, p=0.4245
+  (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 n.s. -- slopes parallel (no differential learning rate) (p=0.2414, slope diff=+1.20)
+Paper (N=24): interaction t(227)=2.68, F(1)=7.12, p=0.008.