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We have given a summary of the number of studies by test type and reference standard (microscopy or PCR) inTable Table 3.
As it is unclear how patients trade off health gains against test burden, represented by test type and frequency, we did not impose functional restrictions on this.
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Is there any bias interaction of rater by test type, rater by test-taker and test-taker by test type?
This section addressed the bias analyses of the interactions of rater by test type, rater by test-taker and test-taker by test type.
FACETS provides estimates of test-taker ability, item difficulty as well as biased interactions between elements of the different facets (e.g., rater by test type, rater by test-taker and test-taker by test type).
The second part reports the bias interaction of a) rater by test type, b) rater by test-taker and c) test-taker by test type.
Overall, no differences were found when analyzed by test type of specimen collection, educational level, having performed an HIVST and type of approach.
Table 4 presents the bias analyses of the interaction of rater by test type.
InTable Table 1, assuming prevalences of 5%, 15%and30%0%, the number of missed non-falciparum or P. vivax malaria cases and the number of false positives in a hypothetical cohort of 1000 patients are presented by test type.
The fatigue results based on the classical fatigue analysis is influenced by the test types and specimen size.
This indicates that these two tests are not only similar but also even close to being identical in terms of their test constructs; thus, they do not warrant being distinguished from each other by test types.
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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