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Discover LudwigThe phrase "assessment robustness" is correct and usable in written English.
It can be used in contexts related to evaluating the reliability and validity of assessments or measurements in various fields, such as education or research.
Example: "The study focused on the assessment robustness of the new testing method to ensure accurate results."
Alternatives: "evaluation reliability" or "assessment reliability".
Exact(4)
Assessment robustness of economic and financial; and.
(x) Assessment robustness of economic and financial; and (xi) Stakeholder consultation .
We considered this the more conservative test of assessment robustness.
Here, we refer to assessment robustness as an indication of different levels of factorial invariance and absence of method-related differences in test retest stability.
Similar(56)
An extension of these results to widen the assessment of robustness of the planned design is also presented.
The results can be of great interest for the assessment of robustness in structures where progressive collapse may be triggered by the failure of parallel steel members like, e.g., in the case of cable-stayed or suspension bridges and of large-span 3D trusses subjected to high strain-rate events.
The assessment of robustness of the NIRS method included variation of certain operational and environmental factors at three level (−1, 0, 1) by applying univariate (one-variable-at-a-time, OVAT) and multivariate (multivariate-at-a-time, MVAT) approach to the experimental design.
The assessment of robustness was based on the semi-parametric PWP model's ability to predict the successive times of occurrence of events when the underlying process actually is parametric (specifically a NHPP having log-linear proportional intensity function with one covariate).
The performance evaluation comprises three aspects: payload capacity, quality assessment, and robustness test.
As a result we propose the assessment of robustness as a standard procedure during the characterization of an AD, which can be done by evaluating the similarity of the relationship between accuracy and an AD measure for the two external subsets.
(2010) argue that all analyses of causal associations in observational data should include an assessment of robustness to unmeasured confounding.
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com