Table 2.
Results from mixed-effects location-scale analyses predicting negative mood from NDSS scores and covariates.
| Base Model |
Smoking Frequency Covaried |
|||||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Model/Predictor | Mean Level |
WS-WW Variance |
Mean Level |
WS-WW Variance |
||||||||
| b | SE | P | VR | SE | P | b | SE | P | VR | SE | P | |
| All Records | ||||||||||||
| Intercept | 3.56 | 0.20 | < .001 | 2.42 | 0.23 | < .001 | 3.23 | 0.22 | < .001 | 2.16 | 0.23 | < .001 |
| Gender | −0.34 | 0.15 | .021 | 0.82 | 0.06 | .004 | −0.30 | 0.15 | .044 | 0.83 | 0.06 | .010 |
| 10th Grade | −0.02 | 0.15 | .873 | 0.94 | 0.07 | .411 | 0.04 | 0.15 | .771 | 0.96 | 0.07 | .560 |
| Time | −0.27 | 0.07 | < .001 | 0.78 | 0.02 | < .001 | −0.26 | 0.07 | < .001 | 0.79 | 0.02 | < .001 |
| BS NDSS | 0.15 | 0.10 | .149 | 1.14 | 0.05 | .004 | 0.68 | 0.18 | < .001 | 1.37 | 0.12 | < .001 |
| WS NDSS | 0.17 | 0.06 | .011 | 1.09 | 0.02 | < .001 | 0.24 | 0.08 | .003 | 1.12 | 0.03 | < .001 |
| BS Smoking | -- | -- | -- | -- | -- | -- | −0.18 | 0.05 | < .001 | 0.94 | 0.02 | .017 |
| WS Smoking | -- | -- | -- | -- | -- | -- | −0.03 | 0.02 | .141 | 0.99 | 0.01 | .175 |
| Random Prompts | ||||||||||||
| Intercept | 3.53 | .020 | < .001 | 2.41 | 0.24 | < .001 | 3.20 | 0.22 | < .001 | 2.06 | 0.23 | < .001 |
| Gender | −0.34 | 0.15 | .024 | 0.79 | 0.06 | .001 | −0.29 | 0.15 | .049 | 0.80 | 0.06 | .004 |
| 10th Grade | −0.03 | 0.15 | .852 | 0.93 | 0.07 | .310 | 0.04 | 0.15 | .789 | 0.95 | 0.07 | .507 |
| Time | −0.24 | 0.07 | < .001 | 0.82 | 0.02 | < .001 | −0.22 | 0.07 | .001 | 0.82 | 0.02 | < .001 |
| BS NDSS | 0.15 | 0.10 | .134 | 1.12 | 0.06 | .024 | 0.38 | 0.19 | < .001 | 1.44 | 0.13 | < .001 |
| WS NDSS | 0.18 | 0.07 | .007 | 1.08 | 0.02 | < .001 | 0.24 | 0.08 | .003 | 1.09 | 0.03 | < .001 |
| BS Smoking | -- | -- | -- | -- | -- | -- | −0.18 | 0.05 | < .001 | 0.92 | 0.01 | .002 |
| WS Smoking | -- | -- | -- | -- | -- | -- | −0.02 | 0.02 | .257 | 1.00 | 0.001 | .626 |
Note: BS = between-subjects, WS = within-subjects WS-WW = within-subjects, within-wave, VR = variance ratio. WS-WW variance parameters were estimated using a log-linear model and then exponentiated so that they represent variance ratios (i.e., the ratio of WS-WW variance per one-unit change on the covariate).