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_d6_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 = 6 rats, 30 sessions   raw day coverage: treat 6..10, control 6..10
+(equal day coverage over this window)
+
+==============================================================================
+FULL MODEL SUMMARY -- fitlme
+==============================================================================
+
+Linear mixed-effects model fit by ML
+
+Model information:
+    Number of observations              30
+    Fixed effects coefficients           4
+    Random effects coefficients          6
+    Covariance parameters                2
+
+Formula:
+    behavior ~ 1 + day*stim + (1 | rat)
+
+Model fit statistics:
+    AIC       BIC       LogLikelihood    Deviance
+    231.74    240.15    -109.87          219.74  
+
+Fixed effects coefficients (95% CIs):
+    Name                   Estimate    SE        tStat      DF    pValue    
+    {'(Intercept)'}        75.867      5.1856      14.63    26    4.6141e-14
+    {'day'        }        3.1667      1.4985     2.1132    26      0.044334
+    {'stim'       }        12.667      7.3335     1.7272    26      0.095989
+    {'day:stim'   }             1      2.1192    0.47188    26       0.64095
+
+
+    Lower       Upper 
+      65.208    86.526
+    0.086483    6.2469
+     -2.4075    27.741
+      -3.356     5.356
+
+Random effects covariance parameters (95% CIs):
+Group: rat (6 Levels)
+    Name1                  Name2                  Type           Estimate
+    {'(Intercept)'}        {'(Intercept)'}        {'std'}        6.3444  
+
+
+    Lower     Upper 
+    2.9639    13.581
+
+Group: Error
+    Name               Estimate    Lower     Upper 
+    {'Res Std'}        8.2076      6.1852    10.891
+
+
+effect                     t(df) / F(df1)     p (resid)    Satterthwaite: p (df)
+----------------------------------------------------------------------------
+stim x day (interaction)   t(26)=  0.47 F(1)=  0.223  p=0.6409    p=0.6413 (df=24)
+day (learning)             t(26)=  2.11 F(1)=  4.466  p=0.04433    p=0.04517 (df=24)
+stim (main, window start)  t(26)=  1.73 F(1)=  2.983  p=0.09599    p=0.1083 (df=13)
+interaction 95% CI: [-3.36, +5.36]
+HONEST LME (per-animal random slope, day|rat): interaction F(1,6.0)=0.18, p=0.6872
+  (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=0.6409, slope diff=+1.00)
+Paper (N=24): interaction t(227)=2.68, F(1)=7.12, p=0.008.