# Table 2 Stepwise multiple regression models: telencephalon components

Telencephalon components (dependent variables)
Independent variables included in the best modeL Septum Striatum Amygdala Schizocortex Hippocampus Neocortex
Total brain volume minus the dependent component b = 0.838 b = 0.947 b = 0.581 b = 0.856 b = 0.812 b = 1.405
t = 19.986 t = 18.384 t = 8.978 t = 13.085 T = 12.946 t = 21.420
p << 0.001 p << 0.001 p << 0.001 p << 0.001 p << 0.001 p << 0.001
Sexual dimorphism b = -0.212 b = -0.373 b = 0.363 b = -0.542 -- --
t = -2.892 t = -4.258 t = 3.308 t = -4.731
p = 0.010 p < 0.001 p = 0.004 p < 0.001
Female group size -- -- -- -- b = -0.117 b = 1.136
T = -2.268 t = 3.398
p = 0.036 p = 0.003
Male group size b = -0.071 -- -- b = -0.188 -- b = -0.058
t = -3.053    t = -5.191   t = -1.984
p = 0.007    p << 0.001   p = 0.064
Whole model F(3,17) = 158.25 F(2,18) = 182.92 F(2,18) = 77.256 F(3,17) = 67.947 F(2,18) = 84.643 F(3,17) = 409.79
R2 = 0.965 R2 = 0.953 R2 = 0.896 R2 = 0.923 R2 = 0.4907 R2 = 0.986
p << 0.001 p << 0.001 p << 0.001 p << 0.001 p << 0.001 p << 0.001
1. The table shows results from separate multiple regression models based on independent contrasts investigating the effects of four independent variables on seven different main components of the primate telencephalon.
2. The models were constructed by sequentially removing variables, keeping those with p ≤ 0.1. Each column contains one best regression model relating to that specific telencephalon component. Numbers to the right of each independent variable are the partial regression coefficients for that specific variable, while the numbers in the bottom row give statistics for the multiple regression models. Dashes indicate variables excluded from the final best models because they had a partial regression p > 0.1.