Skip to main content
Advertisement
Browse Subject Areas
?

Click through the PLOS taxonomy to find articles in your field.

For more information about PLOS Subject Areas, click here.

< Back to Article

Table 1.

The following model was selected with AIC for total brain size as the dependent variable.

More »

Table 1 Expand

Table 2.

The following model was selected with AIC for neocortex size as the dependent variable.

More »

Table 2 Expand

Table 3.

Number of models in which each predictor was estimated non-significant (p > 0.05) with total brain size as the dependent variable.

N = 40.

More »

Table 3 Expand

Table 4.

Number of models in which each predictor were estimated non-significant (p > 0.05) with Neocortex size as the dependent variable.

N = 40.

More »

Table 4 Expand

Table 5.

Changes in p-value for each predictor when altering concomitant predictors using total brain as dependent variable.

Read as follows: the focal predictor in the first column was estimated to a lowest p-value (out of all the 32 models the focal predictor where included in) shown in the second column when using concomitant predictors shown in column three. Likewise, the maximum p-value shown in column four, were estimated using concomitant predictors in column five. N = 40.

More »

Table 5 Expand

Table 6.

The change in p-value for each predictor when altering concomitant predictors using neocortex size as dependent variable.

Read as follows: the focal predictor in the first column was estimated to a lowest p-value (out of all the 32 models the focal predictor where included in) shown in the second column when using the concomitant predictors shown in column three. Likewise, the maximum p-value shown in column four, were estimated using concomitant predictors in column five. N = 40.

More »

Table 6 Expand

Table 7.

Overview of changes in the relation between brain size and predictors as different data is used.

N is identical to the original studies in all re-analyses.

More »

Table 7 Expand