When considering all factors in Model 3, all effects remain significant, indicating that attention to working and commuting times can complement attention to wages and wage satisfaction to increase employees' intention to stay.
Even though district-level variables explain more than 70percentt of the variation in forest disturbance in our econometric model, we find that regional-level effects remain statistically significant.
Although each of these themes has seen considerable attention in the modeling and forecasting communities, their joint effects remain little explored and poorly understood.
The main effects remain stable when including interaction terms into the model.
But some of the psychological effects remain.
Linear regression models showed similar results, but effects remained significant for model 3 (Supplementary Table 3).
Neither analysis found evidence for the postulated serially mediated indirect effects (first model indirect effect =.0010, 95% CI: −.0018,.0064; second model indirect effect =.0010, 95% CI: −.0015,.0060) and both direct effects remained significant (first model direct effect =.1063, 95% CI .0522,.1604; second model direct effect =.2508, 95% CI .1967,.3049).
However, neither analysis found evidence for the postulated serial indirect effects (first model indirect effect =.0044, 95% CI: −.0006,.0138; second model indirect effect =.0016, 95% CI: −.0001,.0054) and both direct effects remained significant (first model direct effect =.1344, 95% CI .0782,.1905; second model direct effect =.0861, 95% CI .0462,.1260).
This simplification procedure was repeated until all effects and interactions in the model were significant with the exception that nonsignificant effects remained in the model if they were dependent effects of a significant interaction.
