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In order to evaluate the measurement quality of our items, we calculated item difficulties and discrimination parameters in terms of Classical Test Theory.
We calculated item difficulty on each test by dividing the number of correct responses for each item by the total number of responses for that item (Crocker and Algina 1986).
We calculated item difficulty on the pretest across both treatments by dividing the number of correct responses for each item by the total number of responses for that item (Crocker and Algina 1986) in order to compare our populations with those reported previously (Price et al. 2014).
To evaluate breadth of coverage, we calculated item distributions and percentage at the ceiling and floor for each scale of the full item bank compared with the WOMAC.
We calculated item difficulty (P) and item discrimination (D) indices for each version of the DCI in the main study, but include only the values for the final round of testing.
We calculated item and scale CVI which allows for focus on consensus rather than consistency estimates and used an adequate number of content experts during the judgment stage [ 28].
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To further interrogate internal consistency, we calculated item-total correlations for each item.
To further explore the consistency of the PHI, we calculated item-total correlations of the PHI for each country.
To further understand the internal consistency of the tool, we calculated item-total correlations for each item.
For validation we performed a principal components analysis (PCA) of the PPQ ICU survey results and then calculated item-total correlations and Cronbach's Alpha for identified factors.
We also calculated item-total correlations which represent the correlation of a single item with the sum of all other items.
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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