Suggestions(1)
Exact(2)
In a replication, the list and name recall data for Level 1 and Level 2 for the three groups (AT, IT, controls) were examined in a multivariate analysis exploring pretest to posttest-2 change.
In this study, reasonable consistency between estimated fractions of MeHg exposure from oceanic fish based on hair Hg isotope ratios and dietary recall data for oceanic and mixed fish consumers suggests that Hg isotopes show promise as a tool for estimating different MeHg exposure sources.
Similar(58)
For the 7.5% of participants (n = 26) who completed only one recall, data from this single recall were used in place of mean intake.
The reliability and validity of such recall data is high for the first 36 months and decreases after that [ 62].
We defined usual intake of selected dietary components (saturated fat, solid fat, high-fat dairy, meat, and refined grains) using the 24-h recall dietary assessment, averaging with a second day of recall data when available for the 2003 to 2004 and 2005 to 2006 cycles (12).
We compare these results to dietary recall data on seafood consumption for the same individuals.
Consumption of vitamin-A rich foods: Data on consumption of vitamin-A rich foods were also drawn from the 24-hour recall data on dietary consumption for the most recently born child under the age of 3, described above.
In order to reduce the need for retrospective recall, data were collected in real-time using hand-held computers [ 22].
Nevertheless, 24-h recall data have not been used for RTEC consumption categorisation since they are only a snapshot of two random days.
An remaining open question is what criteria is used to define "similar" when trying to extract data representations for indexing purposes (recall, data points that are semantically similar will have similar data representations in a specific distance space).
Additional covariates were included in the model to account for whether the recall data was from a weekday or weekend and whether it was the first or second recall [ 25, 26].
Write better and faster with AI suggestions while staying true to your unique style.
Since I tried Ludwig back in 2017, I have been constantly using it in both editing and translation. Ever since, I suggest it to my translators at ProSciEditing.

Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com