Post by lshall on Sept 3, 2014 14:45:02 GMT
Hello,
I am trying to calculate the variance explained by a fixed effect for my binary trait using the liability scale. I have run a null model (covarying for sex, age, age^2, 10 PCs) and alternative model (covarying for sex, age, age^2, 10 PCs and fixed effect of interest). To calculate the variance explained I want to use:
(residual variance (null) - residual variance (alt)) / residual variance (null)
However, it is not apparent how to get an estimate for residual variance on the liability scale.
My output (for the alternative model) is:
Source Variance SE
V(G) 0.000000 0.003491
V(e) 0.142612 0.004045
Vp 0.142612 0.002087
V(G)/Vp 0.000001 0.024482
The estimate of variance explained on the observed scale is transformed to that on the underlying scale:
(Proportion of cases in the sample = 0.180701; User-specified disease prevalence = 0.130000)
V(G)/Vp_L 0.000002 0.047268
logL 4395.453
logL0 4395.453
LRT 0.000
df 1
Pval 0.5
n 9358
Fix_eff SE
0.187804 0.0396742
0.0852184 0.231005
0.832898 0.325876
0.517721 0.341147
0.138649 0.350247
0.0460671 0.374995
1.01668 0.389924
0.538123 0.400774
0.581496 0.417812
0.909118 0.431171
-0.25923 0.436228
0.00589399 0.00161465
-9.56252e-05 1.59942e-05
0.0148662 0.00396532
-0.0872961 0.0079284
Also (on a more basic note!), if I was wanting to perform a likelihood ratio test between this output and the output of my null model, I wasn't sure which logL to use, presumably logL rather than logL0?
Thanks in advance for any advice!
Lynsey
I am trying to calculate the variance explained by a fixed effect for my binary trait using the liability scale. I have run a null model (covarying for sex, age, age^2, 10 PCs) and alternative model (covarying for sex, age, age^2, 10 PCs and fixed effect of interest). To calculate the variance explained I want to use:
(residual variance (null) - residual variance (alt)) / residual variance (null)
However, it is not apparent how to get an estimate for residual variance on the liability scale.
My output (for the alternative model) is:
Source Variance SE
V(G) 0.000000 0.003491
V(e) 0.142612 0.004045
Vp 0.142612 0.002087
V(G)/Vp 0.000001 0.024482
The estimate of variance explained on the observed scale is transformed to that on the underlying scale:
(Proportion of cases in the sample = 0.180701; User-specified disease prevalence = 0.130000)
V(G)/Vp_L 0.000002 0.047268
logL 4395.453
logL0 4395.453
LRT 0.000
df 1
Pval 0.5
n 9358
Fix_eff SE
0.187804 0.0396742
0.0852184 0.231005
0.832898 0.325876
0.517721 0.341147
0.138649 0.350247
0.0460671 0.374995
1.01668 0.389924
0.538123 0.400774
0.581496 0.417812
0.909118 0.431171
-0.25923 0.436228
0.00589399 0.00161465
-9.56252e-05 1.59942e-05
0.0148662 0.00396532
-0.0872961 0.0079284
Also (on a more basic note!), if I was wanting to perform a likelihood ratio test between this output and the output of my null model, I wasn't sure which logL to use, presumably logL rather than logL0?
Thanks in advance for any advice!
Lynsey
