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>
158 lines
5.7 KiB
Plaintext
158 lines
5.7 KiB
Plaintext
==============================================================================
|
|
PHASED days x tDCS LME -- mergeA2 (Box-B2 vs Box-A2)
|
|
==============================================================================
|
|
model per phase: success ~ dayp*tDCS + (1|subject) [dayp = day - phaseStart]
|
|
|
|
phase N A2slp B2slp day p tDCS p intP(res) intP(Satt) intP(RS) slopeDiff [95% CI]
|
|
--------------------------------------------------------------------------------------------------------
|
|
0-5 8 10.54 15.16 1.5e-10 0.693 0.014 0.014 0.089 +4.62 [+1.00,+8.24]
|
|
6-10 7 3.17 4.83 0.035 0.127 0.390 0.390 0.466 +1.66 [-2.22,+5.53]
|
|
6-13 7 2.92 4.47 0.00032 0.125 0.118 0.118 0.303 +1.55 [-0.41,+3.52]
|
|
|
|
Columns: intP(res)=observation-level DF (anticonservative); intP(Satt)=Satterthwaite
|
|
DF (~= residual on this random-intercept model); intP(RS)=per-animal random-slope
|
|
(dayp|subject) model, the honest test (DF collapses toward the animal count; 'n/a' if it
|
|
did not converge). The early phase carries the Box-B2 faster-acquisition signal; late
|
|
phases converge.
|
|
==============================================================================
|
|
FULL MODEL SUMMARY -- phase 0-5: success ~ dayp*tDCS + (1|subject)
|
|
==============================================================================
|
|
|
|
Linear mixed-effects model fit by ML
|
|
|
|
Model information:
|
|
Number of observations 48
|
|
Fixed effects coefficients 4
|
|
Random effects coefficients 8
|
|
Covariance parameters 2
|
|
|
|
Formula:
|
|
success ~ 1 + dayp*tDCS + (1 | subject)
|
|
|
|
Model fit statistics:
|
|
AIC BIC LogLikelihood Deviance
|
|
381.01 392.23 -184.5 369.01
|
|
|
|
Fixed effects coefficients (95% CIs):
|
|
Name Estimate SE tStat DF pValue
|
|
{'(Intercept)'} 10.06 4.465 2.253 44 0.029296
|
|
{'dayp' } 10.543 1.27 8.3016 44 1.4943e-10
|
|
{'tDCS' } -2.5119 6.3144 -0.3978 44 0.6927
|
|
{'dayp:tDCS' } 4.6214 1.796 2.5731 44 0.013526
|
|
|
|
|
|
Lower Upper
|
|
1.061 19.058
|
|
7.9834 13.102
|
|
-15.238 10.214
|
|
1.0018 8.2411
|
|
|
|
Random effects covariance parameters (95% CIs):
|
|
Group: subject (8 Levels)
|
|
Name1 Name2 Type Estimate
|
|
{'(Intercept)'} {'(Intercept)'} {'std'} 4.5394
|
|
|
|
|
|
Lower Upper
|
|
1.7406 11.838
|
|
|
|
Group: Error
|
|
Name Estimate Lower Upper
|
|
{'Res Std'} 10.625 8.5345 13.229
|
|
|
|
|
|
==============================================================================
|
|
FULL MODEL SUMMARY -- phase 6-10: success ~ dayp*tDCS + (1|subject)
|
|
==============================================================================
|
|
|
|
Linear mixed-effects model fit by ML
|
|
|
|
Model information:
|
|
Number of observations 35
|
|
Fixed effects coefficients 4
|
|
Random effects coefficients 7
|
|
Covariance parameters 2
|
|
|
|
Formula:
|
|
success ~ 1 + dayp*tDCS + (1 | subject)
|
|
|
|
Model fit statistics:
|
|
AIC BIC LogLikelihood Deviance
|
|
265.24 274.57 -126.62 253.24
|
|
|
|
Fixed effects coefficients (95% CIs):
|
|
Name Estimate SE tStat DF pValue
|
|
{'(Intercept)'} 75.867 4.9313 15.385 31 4.6291e-16
|
|
{'dayp' } 3.1667 1.4366 2.2043 31 0.035054
|
|
{'tDCS' } 10.233 6.5234 1.5687 31 0.12687
|
|
{'dayp:tDCS' } 1.6583 1.9004 0.87262 31 0.38958
|
|
|
|
|
|
Lower Upper
|
|
65.809 85.924
|
|
0.23676 6.0966
|
|
-3.0713 23.538
|
|
-2.2176 5.5342
|
|
|
|
Random effects covariance parameters (95% CIs):
|
|
Group: subject (7 Levels)
|
|
Name1 Name2 Type Estimate
|
|
{'(Intercept)'} {'(Intercept)'} {'std'} 5.9837
|
|
|
|
|
|
Lower Upper
|
|
2.9396 12.18
|
|
|
|
Group: Error
|
|
Name Estimate Lower Upper
|
|
{'Res Std'} 7.8684 6.0554 10.224
|
|
|
|
|
|
==============================================================================
|
|
FULL MODEL SUMMARY -- phase 6-13: success ~ dayp*tDCS + (1|subject)
|
|
==============================================================================
|
|
|
|
Linear mixed-effects model fit by ML
|
|
|
|
Model information:
|
|
Number of observations 50
|
|
Fixed effects coefficients 4
|
|
Random effects coefficients 7
|
|
Covariance parameters 2
|
|
|
|
Formula:
|
|
success ~ 1 + dayp*tDCS + (1 | subject)
|
|
|
|
Model fit statistics:
|
|
AIC BIC LogLikelihood Deviance
|
|
367.22 378.69 -177.61 355.22
|
|
|
|
Fixed effects coefficients (95% CIs):
|
|
Name Estimate SE tStat DF pValue
|
|
{'(Intercept)'} 76.4 4.9765 15.352 46 1.0096e-19
|
|
{'dayp' } 2.9189 0.74973 3.8932 46 0.00031772
|
|
{'tDCS' } 10.289 6.5773 1.5643 46 0.12459
|
|
{'dayp:tDCS' } 1.554 0.97562 1.5928 46 0.11805
|
|
|
|
|
|
Lower Upper
|
|
66.382 86.417
|
|
1.4097 4.428
|
|
-2.9502 23.528
|
|
-0.40985 3.5178
|
|
|
|
Random effects covariance parameters (95% CIs):
|
|
Group: subject (7 Levels)
|
|
Name1 Name2 Type Estimate
|
|
{'(Intercept)'} {'(Intercept)'} {'std'} 7.1357
|
|
|
|
|
|
Lower Upper
|
|
3.9247 12.974
|
|
|
|
Group: Error
|
|
Name Estimate Lower Upper
|
|
{'Res Std'} 7.3202 5.9279 9.0395
|
|
|
|
|