Sentence examples for samples using multivariate from inspiring English sources

Three spatially exhaustive datasets (a laser-scanned digital elevation model, airborne gamma radiation scanning data and a legacy Quaternary deposit map) were calibrated against topsoil texture and SOM content in around 13,500 soil samples, using multivariate adaptive regression splines (MARSplines) modelling.

The present study was carried out during dry and wet seasons from close by hand-dug wells neighboring Ajakanga solid waste disposal site for better understanding of spatial and seasonal variability of physicochemical parameters, hydro-geochemical facies of groundwater and identification of contamination sources that may affect the groundwater samples using multivariate statistical approach.

Due to the inherent quantitative nature of NMR, we were able to utilise this spectral information in two distinct ways; firstly for the classification and characterisation of samples using multivariate statistical analyses and secondly, the identification and subsequent quantification of metabolites present in the media.

This work proposes a simple and inexpensive electroanalytical method to identify adulteration in hydrated ethyl alcohol fuel (HEAF) samples by using multivariate analysis.

The following two pairs of longitudinal and cross-sectional large-sample studies using multivariate logistic regression analysis illustrate this variability: benzodiazepine users were 2.13 times more likely than non-users to report depressive symptoms at 10-year follow-up [ 6], and 6.7 more likely to report emotional or nervous problems [ 63].

The presence/absence data of all samples were analysed using multivariate analyses (similar in approach to [3], [13], [54], [64], [65] using PRIMER-e (version 6.0; Clarke 1993).

Fifteen (10 training, 5 validation) samples were imputed using multivariate imputation chain equations.

For soils and water, small sample sizes (n = 3/site) prohibited us from using multivariate analyses.

An exploratory correlative study analyzing pretreatment serum samples using a multivariate protein mass spectrometry-based test (VeriStrat®), previously shown to correlate with outcomes in lung cancer patients treated with erlotinib, was performed.

In this paper, we will not deal with studies based on large samples of sites and using multivariate modelling, for which Bayesian approaches were proposed in the recent period [4, 30, 35, 37].

The samples were then analyzed using multivariate statistic tools for further research.