table of contents
The aim of this paper was to investigate the relationship between selection …

Home » Biology Articles » Zoology » Primatology » Primate brain architecture and selection in relation to sex » Tables
Tables
 Primate brain architecture and selection in relation to sex
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 
p 
p 
p 
p 
p 
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 

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 
p 
p 
p 
p 
p 
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


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 
p 
p 
p 
p 
p 
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 
p = 0.004

p 


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 

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 
p 
p 
p 
p 
p 
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


rating: 0.00 from 0 votes  updated on: 23 Oct 2007  views: 7047 
