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

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