Table 2.
Unstandardized estimates (posterior means), 95% credibility intervals (CIs), and effect sizes (f2) from the conditional multilevel model
Between-person predictors of random effects | |||||||
---|---|---|---|---|---|---|---|
Estimated mean | Externalizing Factor | f2 | Internalizing Factor | f2 | |||
PA mean intensity (mean; μPA) | 1.85 [1.66, 2.05] | −0.04 [−0.42, 0.34] | .01 | −0.05 [−0.29, 0.18] | .01 | ||
NA mean intensity (mean; μNA) | 1.25 [1.18, 1.33] | −0.03 [−0.18, 0.12] | .01 | 0.17 [0.07, 0.27] | .10 | ||
PA inertia (autoregression; ΦPP) | 0.47 [0.38, 0.55] | −0.24 [−0.40, −0.08] | .08 | 0.05 [−0.06, 0.14] | .01 | ||
NA inertia (autoregression; ΦNN) | 0.45 [0.35, 0.54] | −0.04 [−0.23, 0.14] | .01 | 0.06 [−0.06, 0.17] | .02 | ||
NAt-1→PAt augmentation (cross-lag; ΦPN) | −0.18 [−0.30, −0.08] | −0.02 [−0.21, 0.17] | .01 | 0.01 [−0.10, 0.12] | .01 | ||
PAt-1→NAt augmentation (cross-lag; ΦNP) | −0.04 [−0.06, −0.02] | 0.002 [−0.04, 0.04] | .01 | −0.02 [−0.04, 0.01] | .04 | ||
PA variability (innovation variance; log(πPA)) | −1.84 [−2.19, −1.48] | 0.71 [0.01, 1.42] | .04 | −0.47 [−0.91, −0.04] | .04 | ||
NA variability (innovation variance; log(πNA)) | −4.22 [−4.74, −3.72] | 0.06 [−0.93, 1.06] | .01 | 0.97 [0.37, 1.58] | .08 | ||
Polarization (negative covariance of innovations; log(ψ)) | −3.91 [−4.36, −3.46] | 0.66 [−0.25, 1.56] | .03 | 0.18 [−0.40, 0.76] | .02 |
Note. N = 156 (17,465 observations). CIs are presented in brackets. Bold type indicates effects that are statistically significant based on CIs that do not include zero. Effect sizes (f2) were calculated for effects of internalizing and externalizing based on model R2 values from models with and without each of these variables (see Supplemental Materials for all conditional model results and R2 values). Effects of covariates (i.e., time at the within-person level; race/ethnicity and low SES at the between-person level) and covariances among predictors and dependent variables (random effects) were also estimated (see Supplemental Materials for these parameter estimates and fully standardized results for all conditional models).