Table 1 

Stepwise multiple regression models: brain components 

Brain components (dependent variables) 



Independent variables included in the best model 
Pons 
Medulla oblongata 
Cerebellum 
Mesencephalon 
Diencephalon 
Telencephalon 


Total brain volume minus the dependent variable 
b = 1.233 
b = 0.734 
b = 1.030 
b = 0.646 
b = 0.841 
b = 1.090 
t = 21.016 
t = 17.239 
t = 22.734 
t = 20.520 
t = 30.225 
t = 28.424 

p << 0.001 
p << 0.001 
p << 0.001 
p << 0.001 
p << 0.000 
p << 0.001 

Sexual size dimorphism 
b = 0.240 
b = 0.369 
 
b = 0.168 
b = 0.140 
b = 0.182 
t = 2.421 
t = 5.093 
t = 3.134 
t = 3.294 
t = 3.227 

p = 0.026 
p << 0.001 
p = 0.006 
p = 0.005 
p = 0.005 

Female group size 
 
 
 
 
b = 0.064 
b = 0.119 
t = 2.143 
t = 3.259 

p = 0.048 
p = 0.005 

Male group size 
 
 
 
 
b = 0.043 
b = 0.062 
t = 2.021 
t = 2.335 

p = 0.060 
p = 0.033 



Whole model 
F_{(2,18) }= 258.21 
F_{(2, 18) }= 260.89 
F_{(1,19) }= 516.82 
F_{(2,18) }= 317.32 
F_{(4,16) }= 409.56 
F_{(4,16) }= 352.48 
R^{2 }= 0.966 
R^{2 }= 0.967 
R^{2 }= 0.964 
R^{2 }= 0.972 
R^{2 }= 0.990 
R^{2 }= 0.989 

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 six different main components of the primate brain. 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 brain component. Numbers to the right of each independent variable are the partial regression coefficients for that specific variable, and 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 