Sentence examples for sampling categories from inspiring English sources

The specific sampling categories used to identify these data sharing platforms were as follows: 1) sector (public, private, or public-private initiatives), 2) primary goal (health research or health data sharing), 3) country specificity (national and cross-national), 4) platform leadership (patient-led or researcher-led approach).

This will allow the researchers to examine and explore directions within the data that will bring about maximum returns, and to further develop and saturate the sampling categories originally identified.

In this study we show that the most common MLVA genotype in both animal and environmental samples obtained from 45 farm locations is MLVA genotype A. The environmental sampling categories, surface swabs and aerosols, are of particular interest for establishing a source hypothesis of C. burnetii infection, since they may provide the link between C. burnetii in animals and humans.

[Categories for wAs reflect study sampling categories and the Bangladeshi As standard of 50 μg/L, whereas categories for bAs and uAs are quintiles.] Mean [H]-methyl incorporation levels were similar between the lowest two wAs categories and among the lowest three uAs quintiles.

b Long-term users of menopausal hormones and diabetics were over-sampled, thus logistic regression models are conditioned for age- and sampling category, which means that only those with complete information about hormone use and diabetes mellitus were included.

Those numbers are calculated as the sum of all employees in the population within a sampling category (by country, sector, firm size, and sometimes region, depending on the sampling strata) divided by the number of observations in that category.

For example, in the sampling category for rows 2 4 and 7, the signal model is typically deterministic although stochastic models could also be envisioned [36].

These experiments are particularly useful to understand the MAC layer mechanisms, such as wake-up or data collisions for the preamble sampling category, and the energy wasted by collisions is evaluated.

Ten women who matched each sampling category were selected for the sample.

Fig. 2 Average relative read abundance (n = 13) of the most abundant genera common for all six sample categories.

Based on structural risk minimization theory, SVMs generate an optimal classification hyperplane, which maximizes the margin between the hyperplane and the nearest samples of the classified sample categories and sets an equal margin.