The Cochrane Collaboration’s tool for assessing risk of bias in randomised trials

By Julian P T Higgins, Douglas G. Altman, P. Gøtzsche, Peter Jüni, David Moher, A. Oxman, Jelena Savović, K. F. Schulz, L. Weeks, J. Sterne. British medical journal, 2011

1,936 citations recorded by the source corpus.

Flaws in the design, conduct, analysis, and reporting of randomised trials can cause the effect of an intervention to be underestimated or overestimated. The Cochrane Collaboration’s tool for assessing risk of bias aims to make the process clearer and more accurate

Subfields: Economics and Econometrics, General Health Professions, Statistics and Probability

View Paper: https://www.semanticscholar.org/paper/a4a6b405f17713d0e876e91d8812eb4628334491

Citations in the corpus

• RoB 2: a revised tool for assessing risk of bias in randomised trials (2019, neutral): “We followed the principles adopted for development of the original RoB tool and for the ROBINS-I tool for assessing risk of bias in non-randomised studies of interventions.(2) 9 A core group coordinated development of the tool, including recruitment of collaborators,”
• A dose of nature: Two three-level meta-analyses of the beneficial effects of exposure to nature on children's self-regulation (2019, neutral): “…= t -test statistic of the difference between the mean r or d and zero; protocol, such as how participants were allocated to different conditions and whether allocation was concealed (for experimental studies) or selective reporting (based on Higgins et al., 2011, see also; Tillmann et al., 2018).”
• Comparative effects of 18 antipsychotics on metabolic function in patients with schizophrenia, predictors of metabolic dysregulation, and association with psychopathology: a systematic review and network meta-analysis (2020, neutral): “Tool for Assessing Risk of Bias.(23) The following domains will be considered:”