Sentence examples for use of appropriate models from inspiring English sources

Specific analysis procedures and the use of appropriate models allowed us to determine the indentation modulus and hardness of the hybrid layers reproductively.

In a decision support system for integrated planning and management, the use of appropriate models is important to avoid models being either too simple or too complex.

We conclude that it is vitally important for epidemiologic research to study "interactions" and, in particular, acquired susceptibility to disease through the use of appropriate models of causation.

While successful, this strategy can be extremely labour-intensive and is very reliant on the use of appropriate models to screen for attenuation.

In any case, for an optimal analysis of the cpDNA variation at the population level, possible length homoplasy will need to be considered and the use of appropriate models will be necessary [ 41, 43].

If differences between intervention groups are investigated, outcomes will be adjusted for baseline values through use of appropriate models (linear, logistic, or Poisson regression); however, the p-values for such secondary analyses may not be interpreted as confirmatory findings.

The results show that the size distribution and surface morphologies of nanoparticles can be quite accurately measured by using SAXS with the aid of appropriate models.

Figure 1 offers an example of the type of illustrative aid that can be used to facilitate the rational choice of appropriate models in a given study.

An example of the type of illustrative aid that can be used to facilitate the rational choice of appropriate models is shown in Figure 1.

QTL mapping strategies can easily accommodate hypotheses about sex-specificity of genetic variants, assuming a sufficient number of male and female progeny are available, through the use of appropriate statistical models that accommodate interaction terms, such as regression models where a phenotype is taken as a dependent variable and genotype is an independent or predictor variable.

The factors we have identified include: grid density and local refinement, the numerical approach, performing a time-step study, the use of sub-iterations for temporal accuracy, the appropriate use of temporal damping, and the use of appropriate turbulence models.