Regression analysis showed that the stress manipulation influenced the level of anger and that change in anger predicted post-pain negative affectivity independently of the contribution of maximum pain (model R2 =.31), with 45% of the total model variance accounted for by change in anger and 17% of the total model variance accounted for by maximum pain intensity.
In the nonstress condition only level of pain intensity was an independent predictor of negative affectivity (model R2 =.16), with 69% of the total model variance accounted for by maximum pain intensity.
Between-model variances increase for the future time series compared to the historical ones indicating larger uncertainties in climate change projections.
Collinearity diagnostics did not suggest a problem with multicollinearity in this model (variance inflation factor <1.5 for all included variables).
Such errors have been shown to have relatively minor effect on the estimation of animal-model derived variances for morphological traits [21].
T-tests (planned comparisons based on nested ANOVAs) were calculated for the additive and multiplicative models using variances for the difference and ratio of two independent random variables, respectively.
Test of F in the ANOVA analysis is used for evaluating model variance in residual variance.
Under an assumption of independence of model errors across species, the model error variance for a group or all species combined are computed as the sum of the variances of individual species.
In particular, we modeled the variance for the above three mean equations using GARCH, APARCH, EGARCH, TGARCH, and IGARCH models.
In meta-analysis, fixed-effect models use inverse variances for weights, with dispersion in estimates due solely to stochastic sampling error in each primary study [13, 14].
We generated 677 five-trait sets and implemented factor analytic modeling, estimating specific variances for each trait, and a single common factor.
