2022
DOI: 10.1002/jrsm.1614
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Bias propagation in network meta‐analysis models

Abstract: Network meta-analysis combines direct and indirect evidence to compare multiple treatments. As direct evidence for one treatment contrast may be indirect evidence for other treatment contrasts, biases in the direct evidence for one treatment contrast may affect not only the estimate for this particular treatment contrast but also estimates of other treatment contrasts. Because network structure determines how direct and indirect evidence are combined and weighted, the impact of biased evidence will be determin… Show more

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Cited by 5 publications
(1 citation statement)
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“…Most studies were roughly symmetrically distributed to 2 sides of the midline. [ 72 ] Additionally, the angle between the correction auxiliary line and the midline is small, indicating less possibility of publication bias. Figure 9 C has general symmetry, and most studies were roughly symmetrically distributed to the left of the midline, indicating a small sample effect.…”
Section: Resultsmentioning
confidence: 99%
“…Most studies were roughly symmetrically distributed to 2 sides of the midline. [ 72 ] Additionally, the angle between the correction auxiliary line and the midline is small, indicating less possibility of publication bias. Figure 9 C has general symmetry, and most studies were roughly symmetrically distributed to the left of the midline, indicating a small sample effect.…”
Section: Resultsmentioning
confidence: 99%