Clutch size, however, did not enter in the best models explaining significant proportion of variance of nestling conspicuousness.
Multivariate regression analyses produced models explaining significant portions of the variance in SF-36 subscales, especially physical functioning (R2 = 42%), and also showed that diabetes-related indicators were more important disease predictors, compared to sociodemographic variables.
The socio-demographic factors alone (allowed first in the model), explained significant amounts of variance for all functioning indexes except MSCR (15.1%), ranging from 21.7% to 37.1%.
Covariates were retained if: 1) there was evidence of confounding (estimates of treatment effect differed markedly between adjusted versus unadjusted models); 2) they explained significant variation in the outcome; 3) they improved the precision of the estimates of treatment effect.
Potential confounding characteristics of homes and residents were included as cluster-level or individual-level fixed or time-varying covariates and retained if evidence of confounding occurred (ie, if estimates of treatment effect differed substantially in the adjusted vs unadjusted models, or they explained significant variation in the outcomes).
In the fledgling model, brood identity explained significant proportion of the variance of digit ratios (Table 1).
First, though all models explained a significant amount of variability in effects (as shown by QM), all model fit tests (QE results) were very large and statistically significant.
Both models explained a significant amount of heterogeneity in the math gaps, as indicated by QM 3) = 16.3, p <.05 and QM 2) = 8.0, p <.05, respectively.
Both science models explained a significant amount of effect-size heterogeneity, as respectively indicated by QM 3) = 18.9, p <.05 and QM 2) = 13.8, p <.05.
Each of the groupings of populations examined using the AMOVA models explained a significant portion of the molecular variance.
