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 
R^{2 }= 0.965 
R^{2 }= 0.953 
R^{2 }= 0.896 
R^{2 }= 0.923 
R^{2 }= 0.4907 
R^{2 }= 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:10.1186/17417007520 