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Taking into account the critique of Bland and Altman 18 concerning the correlation coefficient to calculate the inter-rater reliability, we decided to use λ as proposed by Jepsen et al. 19 Lambda can be calculated as follows: λ = 2 ⋅ VAR X − VAR D 2 ⋅ VAR X. VAR denotes the variance of the measurements, and X and D the difference of the measurements of the two raters.
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The threshold of the event is set according to the chi-square distribution that is constructed by the difference of the measurement of the current time and the measurement of the last sampled moment.
Bland and Altman plots were created by plotting the difference between each measurement and the mean difference of the measurement for the intrarater and interrater agreement, to visualize the possible systematic error and random error of the measurements of one examiner (HD) or the difference between the examiners (HD and MW) [ 25].
It can also be seen that while the difference of the RSS measurements from the same AP with different devices is remarkable, the difference of differential RSS measurements is almost the same.
Despite this slight difference, all of the measurements taken outside of homes were <0.5 mG and considered to be very low.
The reference range was obtained using log transformed measurements and back transformed to give limits for the percentage relative difference of the actual measurements.
These limits consist of the mean difference of the paired measurements ± 1.96 times the sample standard deviation of these differences [5 7].
In the Wilcoxon test the difference of the two measurements is calculated for each subject, then the absolute values of the differences are ordered in ranks.
An 'error band' around the mean difference of the two measurements, d, was defined by 95% SRD = d ± SRD [ 44].
The mean difference of the 10 measurements by two testers was less than 1.25° and the limits of agreement ranged from -6.7° to 8.3°.
The difference of the functional measurements between 2D and 3D techniques is statistically significant in RVEDV, RVSV, and RVEF (P < 0.05) and not significant in RVESV (P = 0.74).
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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