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Table 4 Means and standard deviations across 100 replicates of estimated genetic parameters when genetic correlations are not zero

From: Estimation of genetic variance for macro- and micro-environmental sensitivity using double hierarchical generalized linear models

True parameters Estimated parameters (SD)
ρ A int , A v ρ A int , A sl ρ A sl , A v σ A int 2 σ A sl 2 σ A v 2 ρ A int , A v ρ A int , A sl ρ A sl , A v Np
0 0 0 0.315 0.054 0.107 −0.005 0.004 0.012 0
(0.053) (0.015) (0.046) (0.165) (0.155) (0.249)
0.5 0 0 0.303 0.051 0.099 0.554 −0.028 −0.007 1
(0.047) (0.012) (0.048) (0.155) (0.136) (0.203)
0 0.5 0 0.303 0.053 0.094 −0.010 0.508 −0.014 1
(0.056) (0.012) (0.045) (0.200) (0.132) (0.239)
0 0 0.5 0.293 0.052 0.092 0.014 0.021 0.558 2
(0.045) (0.013) (0.034) (0.185) (0.147) (0.208)
0.5 0.5 0.5 0.301 0.053 0.089 0.537 0.517 0.530 6
    (0.051) (0.013) (0.036) (0.171) (0.138) (0.192)  
  1. ρ A int , A v = genetic correlation between additive genetic effects for intercept and environmental variance; ρ A int , A sl = genetic correlation between additive genetic effects for intercept and slope; ρ A sl , A v = genetic correlation between additive genetic effects for slope (macro-environmental sensitivity) and environmental variance (micro-environmental sensitivity); σ A int 2 = additive genetic variance of breeding value for intercept (true value = 0.3); σ A sl 2 = additive genetic variance of breeding value for slope (= macro-environmental sensitivity; true value = 0.05); σ A v 2 = additive genetic variance for environmental variance (= micro-environmental sensitivity; true value = 0.10); Np = number of replicates with covariance structures forced to be positive definite.