. 2012 Jan 23;7(1):e30845. doi: 10.1371/journal.pone.0030845

Table 1. Correlation coefficients (r), first and second Eigenvalues (λ₁, λ₂), covariance between AD and SS (σ_AD,SS), and effect sizes (Consistent versus Orthogonal discrimination in the first testing block, as measured by Cohen's d) for each experiment.

		Correlation Model			Covariance Model		Effect
	r	λ₁	λ₂	σ_AD,SS	λ₁	λ₂	Size
Exp. 1	0.98	1.98	0.02	25.26	51.00	0.47	0.44
Exp. 2	0.81	1.81	0.19	4.17	9.33	1.00	0.43
Exp. 4	0.95	1.95	0.05	20.48	42.13	1.17	0.37
Exp. 5	0.83	1.83	0.17	11.88	26.19	2.43	0.36
Exp. 3	0.83	1.83	0.17	20.93	46.14	4.29	0.12

Correlation Model indicates Eigenvalues calculated from the correlation matrix of the stimulus sets before the simulation, while Covariance Model indicates Eigenvalues calculated from the input covariance matrix before simulations. The order of experiments is intentionally transposed to highlight the robust negative correlation between the second Eigenvalue of the covariance matrix of the experimental stimuli with listener performance.

Table 1. Correlation coefficients (r), first and second Eigenvalues (λ1, λ2), covariance between AD and SS (σAD,SS), and effect sizes (Consistent versus Orthogonal discrimination in the first testing block, as measured by Cohen's d) for each experiment.

Table 1. Correlation coefficients (r), first and second Eigenvalues (λ₁, λ₂), covariance between AD and SS (σ_AD,SS), and effect sizes (Consistent versus Orthogonal discrimination in the first testing block, as measured by Cohen's d) for each experiment.