Sentence examples for poorly matched for from inspiring English sources

A major limitation of this study is that the treatment groups were poorly matched for aetiology.

This steeper slope reflects more "blur" in the images, though it differs from the frequency filtering typical of optical blur, and thus presents the radiologist with stimuli that their vision should a priori be poorly matched for.

Cases that are poorly matched for genetic background may lead to false positives in association studies.

The type of circulating strain was categorized as heterologous if the authors reported that the strain was antigenically drifted or poorly matched for some other reason.

We were unable to identify influenza challenge studies that met our selection criteria in which the challenge strain was heterologous to the vaccine strain; therefore, it was not possible to estimate efficacy measures from experimental challenge study data when the vaccine was poorly matched for comparison.

Sociodemographic characteristics varied between the analysis cohort and children not contributing to the analysis because of loss to follow-up or missing or poorly matched geocodes for addresses precluding estimation of residential exposure [Supplemental Material, Table E-6 (doi:10.1289/ehp.0901232)].

There is significant interest in estimating vaccine efficacy for poorly matched strains because the prepandemic vaccines currently being developed will likely be poorly matched to the pandemic strain when a pandemic strain emerges.

The proportion of exons outside of the 99% confidence interval was reduced to 1.8% for the well-matched pair of exomes and to 2.3% for the poorly matched pair (blue lines in Fig. 1B and C, respectively) To quantify this noise in the sequence data, we defined the statistic as the ratio between the standard errors of the beta-binomial model and the binomial model.

Otherwise, studies tend to get published because of their novelty despite low numbers, poorly matched cases and controls and no multivariate adjustment for conventional risk factors.

Firstly, we attempted matching in a ratio of 1 4 for users and non-users, respectively, but we found matches for less than half of the users and matching yielded only approximately two matches for each user and use groups that were poorly matched; we therefore abandoned this approach.

Even if poorly matched, having two groups with similar, boring names set the stage for the appearance of a two-handed tax debate.