Using techniques that measure overall variation, frequency contribution, scale-invariant variation and degree of disorder, altered variability in consistently present in illness states, and the degree of alteration provides a measure of prognosis.
This past Sunday, a group of researchers reported in the journal, Nature Medicine, a preliminary technique that uses variation in blood levels of 10 fats to predict the likelihood that elderly individuals would develop mild cognitive impairment (MCI) or Alzheimer's Disease in the following 2-3 years.
SSCP is a highly sensitive technique that detects variation in the nucleotide sequences of single-stranded molecules.
The purpose of this study was to analyze the relationships between soil attributes and environmental covariates in a tropical hillslope environment on a regional scale to estimate spatial distribution of soil attributes and identify statistical and geostatistical techniques that could represent the variation of the soil attributes.
In the present study, we applied a rigorous study design to assess sources of both potential confounding and experimental variability (nuisance variation) and analyzed the data using statistical techniques that incorporate nonnested sources of variation (i.e., those not eliminated by normalization) and that return estimates of least variability with accurate inference (linear mixed-effects models).
So scientists must develop accurate techniques that consistently reveal small variations in the interactions between genes and the environment.
Since the electrical properties of crustal material heavily depend on the fluid content, techniques that are sensitive to variations in electrical properties offer plausible solutions to the problem.
In which case, simple count-based methods can be sufficient and allow the experimenter to make use of statistical techniques that appropriately account for the biological variation between samples.
For this reason, spatial analysts should research which current analysis techniques (or variations of such techniques) that have been already successfully applied to other areas (e.g., epidemiology, location-allocation analysis, etc). can also be employed to the spatial analysis of crime data.
In this paper, we present P -wave velocity structure models, derived by traveltime analysis techniques, that clearly show along-trench structural variations within the overlying plate.
