Post by jy on Feb 28, 2014 9:22:45 GMT
Source Variance SE
V(G)_tr1 0.041200 0.023290
V(G)_tr2 0.011848 0.033942
C(G)_tr12 0.022093 0.020905
V(e)_tr1 0.095301 0.023137
V(e)_tr2 0.149957 0.034289
Vp_tr1 0.136501 0.004906
Vp_tr2 0.161805 0.006684
V(G)/Vp_tr1 0.301828 0.169481
V(G)/Vp_tr2 0.073222 0.209652
The estimate of variance explained on the observed scale is transformed to that on the underlying scale:
(Proportion of cases in the sample = 0.170861; User-specified disease prevalence = 0.003000 for disease 1 and = 0.002000 for disease 2)
V(G)/Vp_tr1_L 0.227704 0.127859
V(G)/Vp_tr2_L 0.046395 0.132840
rG 1.000000 1.703423
logL 1235.137
n 2731
Hello, given the above, I'd like to ask about the possibility of rG being 1 between 2 different traits and what could have gone wrong from your experience.
Also would appreciate if you enlighten on possibly why the variance is so large, from your experience.
Appreciate your input...
V(G)_tr1 0.041200 0.023290
V(G)_tr2 0.011848 0.033942
C(G)_tr12 0.022093 0.020905
V(e)_tr1 0.095301 0.023137
V(e)_tr2 0.149957 0.034289
Vp_tr1 0.136501 0.004906
Vp_tr2 0.161805 0.006684
V(G)/Vp_tr1 0.301828 0.169481
V(G)/Vp_tr2 0.073222 0.209652
The estimate of variance explained on the observed scale is transformed to that on the underlying scale:
(Proportion of cases in the sample = 0.170861; User-specified disease prevalence = 0.003000 for disease 1 and = 0.002000 for disease 2)
V(G)/Vp_tr1_L 0.227704 0.127859
V(G)/Vp_tr2_L 0.046395 0.132840
rG 1.000000 1.703423
logL 1235.137
n 2731
Hello, given the above, I'd like to ask about the possibility of rG being 1 between 2 different traits and what could have gone wrong from your experience.
Also would appreciate if you enlighten on possibly why the variance is so large, from your experience.
Appreciate your input...
