Combining estimators in interlaboratory studies and meta-analyses

Many statistical methods (estimators) are available for estimating the consensus value (or average effect) and heterogeneity variance in interlaboratory studies or meta-analyses. These estimators are all valid because they are developed from or supported by certain statistical principles. However, no estimator can be perfect and must have error or uncertainty (known as estimator uncertainty). For a given dataset, the consensus value and heterogeneity variance given by different estimators can often differ significantly. Consequently, the choice of different estimators can affect the conclusion of an interlaboratory study or meta-analysis. However, there is no universally accepted metric for determining which estimator is optimal among a set of candidate estimators. Instead of selecting and using a single estimator, this paper proposes an estimator-averaging approach to combine a set of individual estimators. The final averaged estimator is a linear combination of individual estimators, which accounts for three sources of uncertainties including the estimator uncertainty. Monte Carlo simulations were performed to examine the long-run performance of four individual estimators and the proposed averaged estimators. A case study: the determination of the Newtonian constant of gravitation is presented, where 10 individual estimators (eight frequentist weighted average methods and two Bayesian methods) are combined using the proposed estimator-averaging approach.

First functional analysis of a novel splicing mutation in the B3GALTL gene by an ex vivo approach in Tunisian patients with typical Peters plus syndrome

Peters plus syndrome is a rare recessive autosomal disorder comprising ocular anterior segment dysgenesis, short stature, hand abnormalities and distinctive facial features. It was related only to mutations in the B3GALTL gene in the 13q12.3 region. In this study, we undertook the first functional analysis of a novel c.597-2 A>G splicing mutation within the B3GALTL gene using an ex-vivo approach. The results showed a complete skipping of exon 8 in the B3GALTL cDNA, which altered the open reading frame of the mutant transcript and generated a PTC within exon 9. This finding potentially elicits the nonsense mRNA to degradation by NMD (nonsense-mediated mRNA decay). The theoretical consequences of splice site mutations, predicted with the bioinformatics tool Human Splice Finder, were investigated and evaluated in relation to ex-vivo results. The findings confirmed the key role played by the B3GALTL gene in typical Peters-plus syndromes and the utility of mRNA analysis to understand the primary impacts of this mutation and the phenotype of the disease.

Combining Results From Multiple Evaluations of the Same Measurand

According to the Guide to the Expression of Uncertainty in Measurement (GUM), a result of measurement consists of a measured value together with its associated standard uncertainty. The measured value and the standard uncertainty are interpreted as the expected value and the standard deviation of a state-of-knowledge probability distribution attributed to the measurand. We discuss the term metrological compatibility introduced by the International Vocabulary of Metrology, third edition (VIM3) for lack of significant differences between two or more results of measurement for the same measurand. Sometimes a combined result of measurement from multiple evaluations of the same measurand is needed. We propose an approach for determining a combined result which is metrologically compatible with the contributing results.