Sentence examples for informed variance from inspiring English sources

A simpler and more general approach to incorporating informed variance priors is to borrow strength from external empirical evidence.

The above proposed approach for obtaining and eliciting informed variance priors is either optimal or sub-optimal depending on the assumptions one is willing to make.

Imposing consistency equations on variance estimates, assuming variances to be exchangeable, or using empirically informed variance priors also yielded good model fits and narrow credible intervals.

The informed variance prior approach, however, is sub-optimal if one is not willing to believe the frequentist variance likelihoods and prefers to incorporate additional uncertainty around variance estimation.

Because the amount of evidence to reliably estimate heterogeneity variance parameters is typically sparse, some precision can be gained either by incorporating informative variance priors or by using alternative restrictive heterogeneity variance structures in connection with weakly informed variance priors.

While Trt1 and Trt3 consistently received very low rank probabilities (e.g., 0.5% chance of being the best), the probability of Trt2 versus Trt4 being the best treatment varied from 71.3% versus 28.2% with the homogeneous variance model to informed variance model to 43.2% versus 56.8% with the unrestricted variance model (see Table 5).

The exchangeable variance model and the empirically informed variances model also produced seemingly reliable variance estimates.

In this example, a number of reasons suggest the informed variances model based on frequentist approximate variance distributions is the more optimal choice.

The empirically informed variances model had the second highest posterior distribution precision, the consistency variances model third, the exchangeable variances model fourth, and lastly the unrestricted variances model produced the most imprecise posterior distributions.

The empirically informed variances model had the second highest posterior distribution precision, the consistency variances model third, the exchangeable variances model fourth, and lastly the unrestricted variances model fifth.

For the 'empirically informed variances' model we used a log-normal distribution with mean −2.34 and variance 1.62 [ 2] because all interventions being compared are pharmacological and the outcome, SVR, is a dichotomous biological marker, which fits under 'subjective outcome' definition by Turner et al. [ 6].