Resolution:
## Figure 4.
Raw OLS regression for body mass estimation and percent prediction error of body mass
proxies. (A) The least-squares regression of the raw data between the log total stylopodial circumference
and log body mass in a sample of 245 (talpids removed) mammals and non-avian reptiles.
Regression equation shown in the format y = mx + b, and is presented along with its coefficient of determination (R^{2}), mean percent prediction error (PPE), standard error of the estimate (SEE), and
Akaike Information Criterion (AIC). (B) Comparison of the predictive power of several body mass proxies based on their mean
PPE. The mean PPE of each proxy is represented by the black circle along with their
95% confidence error bars. The plot is divided into two sections representing the
results from the bivariate and multiple regression analyses. Variables regressed against
body mass are labelled along the x-axis. Labels marked with an * represent the analyses
in which the data was phylogenetically adjusted through the use of a phylogenetic
generalized least squares bivariate or multiple regression. C_{F}, femoral circumference; C_{H}, humeral circumference; L_{F}, femoral length; L_{H}, humeral length; OLS, ordinary least squares.
Campione and Evans |