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All items show an unambiguous factor loading pattern in the whole sample (table 4) and in patients with chronic conditions.
A rating of "Somewhat" was given to G5 and G10 as these items show an increase in OCCs after the 50th percentile.
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The items show a good fit to the Rasch model.
Hence, all items show a good to very good fit since they are situated within the strict interval of.80 ≤ wMNSQ ≤ 1.20 postulated for the PISA study (OECD 2014, p. 151).
Scales with more items show a higher proportion of missing data.
One of five pairs of conceptually related items show a high level of association and four pairs show moderate levels of association.
However, the other medical items show a much lower percentage of outsourcing rate such as nutrition, pharmacy, and nursing, the outsourcing rate is lower than 3%.
The confirmatory factor analyses in this study suggest that all items show a substantial contribution to the fitness of the current model.
Preliminary analyses of these items showed an internal consistency of α = 0.91.
Students' performance on the fitness items shows an important difference for how students related the concept of fitness to plants versus animals.
All items showed an extraction communality ≥ 0,45 (range 0,634 to 0,898).
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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