Selected article for: "assignment effect and intended intervention"
Author: Francisca Verdugo-Paiva; Ariel Izcovich; Martin Ragusa; Gabriel Rada
Title: Lopinavir/ritonavir f?or the treatment of COVID-19: A living systematic review protocol
  • Document date: 2020_4_17
    • ID: mhi6w4mr_48
    Snippet: We will assess the risks of bias of other study designs with the ROBINS-I tool (ROBINS-I: Risk Of Bias In Non-randomised Studies of Interventions) [28] . We will assess the following domains: bias due to confounding, bias in selection of participants into the study, bias in classification of interventions, bias due to deviations from intended interventions (effect of assignment to intervention), bias due to missing data, bias in measurement of ou.....
    Document: We will assess the risks of bias of other study designs with the ROBINS-I tool (ROBINS-I: Risk Of Bias In Non-randomised Studies of Interventions) [28] . We will assess the following domains: bias due to confounding, bias in selection of participants into the study, bias in classification of interventions, bias due to deviations from intended interventions (effect of assignment to intervention), bias due to missing data, bias in measurement of outcomes and bias in the selection of the reported result. We will judge each domain as low risk, moderate risk, serious risk, critical risk, or no information, and evaluate individual bias items as described in ROBINS-I guidance. We will not consider time-varying confounding, as these confounders are not relevant in this setting [28] . We will consider the following factors as baseline potential confounders:

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