Table 3.
Multilevel modeling of psychobiological data
| Fixed effects | M1: sCort (covariates) | M2: sCort (+ treatment) | M3: sAA (covariates) | M4: sAA (+ treatment) | ||||
|---|---|---|---|---|---|---|---|---|
| Est | p | Est | p | Est | p | Est | p | |
| INTERCEPT | 0.821 | 0.000 | 0.974 | 0.000 | 4.679 | 0.000 | 4.745 | 0.000 |
| SEQUENCE (0 = MI—> CC, 1 = CC—> MI) | -0.106 | 0.639 | -0.145 | 0.506 | -0.124 | 0.669 | -0.206 | 0.459 |
| TIME (linear: 0, 1, 2, 3) | -0.033 | 0.013 | -0.048 | 0.009 | 0.010 | 0.732 | 0.028 | 0.484 |
| TREAT (0 = CC, 1 = MI) | - | - | -0.048 | 0.678 | - | - | -0.037 | 0.799 |
| SEX (0 = male, 1 = female) | - | - | - | - | -0.826 | 0.010 | -0.761 | 0.015 |
| MED.SEDA (0 = no, 1 = yes) | 0.691 | 0.038 | 0.682 | 0.035 | - | - | - | - |
| MED.CORT (0 = no, 1 = yes) | -0.920 | 0.030 | -0.820 | 0.035 | - | - | - | - |
| TIME SINCE LAST MEAL (minutes) | 0.001 | 0.002 | 0.001 | 0.001 | - | - | - | - |
| TIME*TREAT | - | - | 0.032 | 0.214 | - | - | -0.015 | 0.798 |
| Random effects (variances) | ||||||||
| INTERCEPT L3 (across patients) | 0.303 | - | 0.271 | - | 0.631 | - | 0.613 | - |
| INTERCEPT L2 (across sessions) | 0.186 | - | 0.198 | - | 0.189 | - | 0.200 | - |
| Residual variance | 0.057 | - | 0.059 | - | 0.331 | - | 0.334 | - |
| Model fit | ||||||||
| AIC | 244.104 | - | 271.232 | - | 728.881 | - | 771.726 | - |
| BIC | 276.688 | - | 311.973 | - | 755.215 | - | 806.027 | - |
| N | ||||||||
| Observations (L1) | 276 | - | 300 | - | 318 | - | 334 | - |
| Sessions (L2) | 69 | - | 75 | - | 80 | - | 84 | - |
| Patients (L3) | 38 | - | 38 | - | 40 | - | 42 | - |
Notes: sCort salivary cortisol (log-transformed), sAA salivary alpha-amylase (log-transformed), M model, L level, Est Estimate, MI mindfulness intervention, CC control condition, MED.SEDA sedative medication, MED.CORT corticosteroid medication, AIC Akaike Information Criterion, BIC Bayesian information criterion, bold effects were statistically significant on the level of p < 0.05