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

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.

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.

Lindenfors et al. BMC Biology 2007 5:20   doi:10.1186/1741-7007-5-20