Sentence examples for models in aggregate from inspiring English sources

While it does not represent the effectiveness of all integrative models in aggregate, this study does provide an important foundation for the development and implementation of future integrative models for back pain care.

There has been an ongoing discussion in the econoblogosphere about the usefulness or lack thereof of "microfoundations" in macroeconomics, which in practice means trying to write down models in which aggregate behavior is justified in terms of the actions of utility-maximizing individuals with rational expectations.

Figure 10 shows the goodness-of-fit indices of spatial models in different aggregated scale.

Furthermore, XRD data confirm the molecular packing models in these aggregates.

These were tested in aggregate models and models stratified by type of residence.

Both road safety and socioeconomic variables were entered in the model in their aggregate values.

On the other hand, in the presence of high power amplifiers (HPAs) and square root raised cosine (SRRC) filters, the AWGN channel can be modeled in the aggregate as a nonlinear channel with memory.

It can be seen that the association of father's occupation with CRP lost significance when ICAM and IL-6 were entered into the model, and that in aggregate early life variables did not add to the goodness of fit of the model (F-test for Model 2 versus a model with only age, sex, ICAM and IL-6 was not significant).

These observations have been corroborated in in vivo models where aggregate accumulation is observed in dystrophic neurites.

This difference may be explained by our examining the relationship of all metabolites with each trait in aggregate models, as opposed to separately, or by our having performed the analyses in a longitudinal cohort design as opposed to in a case-control design.

We hypothesized that genetic and metabolite biomarkers of diabetes risk, by capturing different pathogenic elements for type 2 diabetes development, would provide complementary information to each other regarding future diabetes risk and possibly improve clinical models of diabetes prediction in aggregate.