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. 2018 Jun 6;74(1):29–37. doi: 10.1093/geronb/gby068

Table 4.

Multilevel Model Predicting Current Negative Affect From Reported and Lagged Forecasted Stressors and Age When No Stressor Was Previously Reported

Variable B coefficient SE p value
Fixed effects
 Intercept 18.60 1.54 <.01
 Currently reported stressor 15.81 0.99 <.01
 Lagged forecasted stressor 4.78 0.89 <.01
 Interaction between currently reported and lagged forecasted stressors −0.73 1.33 0.58
 Age −0.10 0.10 0.30
 Interaction between currently reported stressor and age −0.21 0.09 0.02
 Interaction between lagged forecasted stressor and age −0.01 0.08 0.89
 Interaction among currently reported stressor, lagged forecasted stressor, and age −0.10 0.12 0.40
 Proportion of reported stressor 1.00 9.10 0.92
 Proportion of forecasted stressor 6.91 7.55 0.36
 Prior (lagged) negative affect centered at day-mean negative affect −0.24 0.01 <.01
 Random effects (variance components)
Level 1 Residual (within-person) 102.68 2.02 <.01
Level 2 Day 44.38 2.58 <.01
Level 3 Residual (between-person) 242.54 23.41 <.01
Reported stressor 138.08 18.94 <.01
Lagged forecasted stressor 33.35 9.77 <.01
Covariance (residual, reported stressor) −32.17 14.65 0.03
Covariance (residual, lagged forecasted stressor) −15.18 12.05 0.21
Covariance (reported stressor, lagged forecasted stressor) 14.16 11.63 0.22

Note: NA = xxx. Age was included as a moderator in order to test for age differences. Age was centered at 45 years old and addressed as a continuous variable. Intercept, currently reported stressor, and lagged forecasted stressor were included as random effects.