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

Table 3 Means and standard deviations of estimated genetic parameters across 100 replicates when genetic correlations are zero

Fixed effects¹	True parameters			Estimated parameters (SD)						Np
Fixed effects¹	$σ A int 2$	$σ A sl 2$	$σ A v 2$	$σ A int 2$		$σ A sl 2$		$σ A v 2$		Np
No	0.1	0.05	0.1	0.101	(0.020)	0.051	(0.012)	0.095	(0.035)	0
No	0.3	0.05	0.1	0.315	(0.053)	0.054	(0.015)	0.107	(0.046)	0
No	0.5	0.05	0.1	0.507	(0.066)	0.052	(0.013)	0.115	(0.061)	3
No	0.3	0.05	0.05	0.297	(0.047)	0.053	(0.012)	0.053	(0.029)	4
No	0.3	0.05	0.2	0.308	(0.049)	0.053	(0.014)	0.186	(0.065)	0
No	0.3	0.025	0.1	0.298	(0.047)	0.026	(0.008)	0.097	(0.041)	0
No	0.3	0.1	0.1	0.296	(0.052)	0.104	(0.021)	0.083	(0.045)	1
Yes	0.1	0.05	0.1	0.099	(0.022)	0.053	(0.014)	0.091	(0.037)	1
Yes	0.3	0.05	0.1	0.309	(0.044)	0.057	(0.015)	0.104	(0.051)	0
Yes	0.5	0.05	0.1	0.503	(0.084)	0.052	(0.014)	0.104	(0.074)	10

¹Models have either only a mean as fixed effect (no fixed effects) or have contemporary groups as fixed effects (yes); $σ A int 2$ = additive genetic variance of breeding value for the intercept; $σ A sl 2$ = additive genetic variance of breeding value for the slope (= macro-environmental sensitivity); $σ A v 2$ = additive genetic variance for environmental variance (= micro-environmental sensitivity); Np = number of replicates with covariance structures forced to be positive definite.

ISSN: 1297-9686