To examine the dependence of soil taxonomic composition on latitude and soil type, we performed ANCOVAs using pairwise dissimilarity indices (two separate response variables), differences in latitude (continuous predictor), and combinations of soil types (categorical predictor).
A multiple regression analysis with mother snout vent-length (SVL) as continuous predictor and the number of top embryos, the number of attached eggs, and clutch size as dependent variables yielded Wilks' λ = 0.51; F3, 18 = 5.71; P = 0.006.
Table 4: Statistical results from a General Linear Model between mean heart rate (continuous predictor), embryo positioning and clutch of origin (categorical predictors), and snout-vent length and body mass at birth (dependent variables).
Table 2: Statistical results of a multiple regression analysis between mother snout vent-length (continuous predictor) and the number of top embryos, the number of attached eggs, and clutch size (dependent variables).
In many applications, the mean of a response variable can be assumed to be a non-decreasing function of a continuous predictor, controlling for covariates.
The dependant variable was injury (injury = 1; non-injury = 0), and the continuous predictor variable was time (in years).
When modeled as a continuous predictor, a U-shaped relationship between systolic BP dipping ratio and future CAC was apparent and persisted after adjustment for multiple potential confounders (P<0.001 for quadratic term).
Linearity of the continuous predictor age was assessed using a linear mixed additive model and by inclusion of polynomial terms in the model.
Future analyses may look at more fine-grained comparisons of all of these participants using map scores as a continuous predictor of eye-movement variability.
The optimal cutoff point of each relevant continuous predictor was assessed by the area under curve (AUC) in receiver operating characteristic (ROC) curve analysis.
We then compared the standard deviations using an analysis of variance (ANOVA) with year as a continuous predictor and disease as a random factor.
