Though it is difficult to assess the impact of sample size, an alternative option is to generate a full distribution of the parameters to determine the uncertainty of estimates. Hence, these sampling variances could be biased if the assumption of asymptotic approximation is incorrect, especially when the sample size is small. This method is based on large sample theory under the assumption that the parameter estimates are asymptotically multivariate normally distributed with covariance matrix given by the inverse of the information matrix. Residual Maximum Likelihood (REML) analysis is the most widely used method to estimate variance components and heritability.