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They are part of a welcome effort to make statistical measures give a more credible picture of a modern economy, as well as to improve international comparability.
Progress-related measures give a good indication of attackers, even though they are not perfect.
Although there is no way to be sure whether the earnings and employment benefits we observe would persist over an extended period (Smith 2011), these measures give a sense of the likely long-term benefits.
Self-reported measures give a good amount of information about individual health since people summarize all the health information they have from their practitioners (general practitioners and specialists) and from what they feel [1].
These measures give a better estimate of the accuracy of connectivity of the predicted transcripts.
Furthermore, previous studies have shown that area-based measures give a good approximation of individual SES [ 40].
Similar(52)
Precision, recall, and F2-measure These three measures give an overview on how pure and how sensitive the model is.
Thus, the class separability and the score reliability (dispersion) or separability measures give an indication of the quality of the biometric samples and the matcher [22].
Thus, the class separability and the score separability measures give an indication of the quality of the biometric samples and the matcher.
Two more measures give an index of the degree of fit of a model to the data.
Those studies that did incorporate these measures gave a lower estimate of treatment efficacy, meaning that the treatment effects were more likely to be accurately estimated.
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com