Post by Jian Yang on Dec 2, 2015 0:30:38 GMT
) is per definition non-negative. However, the estimate of h2
is supposed to be following a normal distribution with mean h2
and variance SE2
where SE is the standard error of the estimate of h2
. Therefore, to get an unbiased estimate of h2
, we should allow the estimate to be negative (--reml-no-constrain option in GCTA-GREML analysis).
In practice, there are a least two scenarios when we would see negative estimate of h2
1) Small sample size. If the sample size is small, the sampling variance (SE2
) will be large. In this case, the estimate of h2
will fluctuate a lot and therefore has a certain chance to jump out of the parameter space (between 0 and 1).
2) The true h2
parameter is small. If h2
is very small, then even if the sample size is large, we will still have a certain probability to see negative estimate.
In the Yang et al. (2013 PLoS Genet)
and Zhu et al. (2015 AJHG)
papers, to get an unbiased estimate of the mean estimate of h2
, we did not constrain the estimate to 0.