Figure 4 - available via license: Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International
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Diagram illustrating user bias (user 1) and inconsistency of bias compared with other users (users 2 and 3).
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User measurement bias during subcutaneous tumor measurement is a source of variation in preclinical in vivo studies. We investigated whether this user variability could impact efficacy study outcomes, in the form of the false negative result rate when comparing treated and control groups.
Two tumor measurement methods were compared; calipers which...
Context in source publication
Context 1
... were also more consistent in their biases when using 3D-TI as opposed to calipers when looking at the standard deviation for large and medium size tumors (Figure 3b, p = 8.3 x 10 -5 and p = 1.6 x 10 -2 respectively, t-test). Figure 4 shows examples of user measurement bias as well as inconsistency of bias. Generating synthetic users 100 synthetic users were generated from measurement data of 15 original users to produce more robust results and reduce effects of outliers (Figure 1, box 1b). ...
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User measurement bias during subcutaneous tumor measurement is a source of variation in preclinical in vivo studies. We investigated whether this user variability could impact efficacy study outcomes, in the form of the false negative result rate when comparing treated and control groups. Two tumor measurement methods were compared; calipers which...
