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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.