Sentence examples for unbiased proportion from inspiring English sources

The mean estimate of the posterior probability distribution of the unbiased proportion of seropositive swine was 0.921 955% CI: 0.797-0.985).

Only one of these studies [ 47] reported an unbiased proportion of shedding among seropositive children 33% (7/21)—but most of the children were older in fact, only five seropositive children were under the age of five, which may, in light of our finding of less shedding among older children, have led to a lower shedding proportion in that study.

The approach will facilitate efficient and parallel characterization of considerable unbiased proportions of multigene family members and their transcripts from nonmodel organisms.

The broad phylogenetic distribution (supplementary fig. 3, Supplementary Material online) and the HORDE family composition (fig. 1 B ) of FLX-based OR sequences for the anole lizard showed that this approach can quickly characterize considerable unbiased proportions of OR gene members from multiple sources in parallel.

Asymmetries and outliers were detected in estimates of ampicillin, co-trimoxazole, ciprofloxacin and multi-drug resistant isolates, but unbiased pooled proportions were not estimated by the Duval and Tweedie method.

Population estimates for the DS method remained unbiased as the proportion of units intensively surveyed changed, but the variance of the estimates decreased with increasing proportion intensively surveyed.

The unbiased diagnostic accuracy (proportion of correct classification) was estimated to 91.24 %, against 92.65 % initially computed on the original dataset.

By reviewing only articles of measured postpartum blood loss, this article provides comparisons unbiased by the proportion of studies using visual compared with measured blood loss.

Yang et al. discovered that estimates of variance explained by genome-wide SNPs are unbiased with the proportion of SNPs used to estimate genetic relationships in human height [ 1].

From these, we estimated the delay from symptom onset to hospitalisation using a parametric mixture survival model, 18 giving an estimate (assumed unbiased) of the proportion of confirmed cases hospitalised, which we used indirectly in our Bayesian analysis.

For simplicity, we assume that we have an unbiased estimate of the proportion of population with pre-existing immunity based on the observed seropositive proportion prior to the epidemic wave in Table 1.