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We believe that our missing data reflect a random process rather than systematic bias.
Missing data reflect that are closed by the front-end advisor as they are related to simple quick-health information-related calls that do not warrant a symptom classification or to be discussed with a nurse advisor.
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Failure assumed for missing data (missing=failure)—assumed that missing data reflected poor outcome, for example, relapse.
Here, groupings in the composition-based NJ tree appear to be largely independent of missing data, reflecting instead real differences in mean composition among taxa.
These simulated datasets have realistic patterns of missing data, reflecting both biological processes and taxon sampling strategies used by systematists in phylogenetic studies.
This high percentage of missing data might reflect the lack of precision of medical prescriptions or the lack of transcription of the nurse on the medical file.
One explanation for this is that high levels of missing data may reflect the difficulties that respondents had in knowing what impedes them from searching for and using new research in practice.
This allows addressing problems that arise with missing data by reflecting item difficulty when calculating person ability scores.
In Study 2, some participants had missing data, which could reflect AMT workers' attempt to complete tasks quickly.
Of whom 4.5% were missing, and hence missing data were already reflected to response rate when calculating weight.
Due to the large sample size, some of the measures have missing data as is reflected in the differing degrees of freedom.
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com