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The complete matrix represents 30 rodents and 7 outgroups with a low amount of missing data (Additional file 3).
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There was a small amount of missing data on place of residence.
There were relatively low amounts of missing data and high participation rates.
The amount of missing data for Beliefs and Dispositions, while not negligible, represents a reasonably small amount of missing data.
Because of the relatively small amount of missing data casewise exclusion of missing cases was performed.
Given the small amount of missing data, missing values were replaced with item means.
We used missing indicator variables for the small amount of missing data.
The small amount of missing data from items were imputed in the maximum likelihood estimation procedures.
The small amount of missing data indicated that respondents found the clinical scenarios plausible.
With relatively small amounts of missing data, a higher precision was achieved, but again, with larger amounts of missing data, some bias occurred.
Small amounts of missing data were mean imputed except for outcome measures.
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CEO of Professional Science Editing for Scientists @ prosciediting.com