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All three measures estimate important network dynamics.
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The analytical models require less computational effort than simulation models, and experimental results show that they accurately estimate important performance measures like average flow time, machine utilization, and setup frequency.
Although long-term (e.g., 365-day) adherence measures are important, estimating adherence over shorter intervals may clarify the course of vulnerability to risk and enable clinicians to better design adherence/risk-related interventions.
Although it has some drawbacks and it is not unanimously accepted by the scientific community, nevertheless we consider that it is one of the most important measures to estimate the impact of scientific published work in the scientific community.
This gives cause for concern as transition questions are used as anchors to estimate minimally important change (MIC) thresholds on patient reported outcome measures such as the RMDQ.
Finally, measures to estimate in utero exposures retrospectively among women diagnosed in their 40s 60s could lead to more informative studies of this important life stage.
Clinicians use several measures to estimate adiposity.
This measure is important to estimate the cost of introducing the new protocol.
How can we measure or estimate exposure?
The transition from seed to seedling is the most vulnerable stage of plant life (Kitajima 2007) and is crucial for a successful restoration from seed; examination of seedling performance is an important measure for estimating fitness differences between plants.
(a) Correlation between measured and estimated measures.
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