Non-collapsible marginal effect measures depend on joint distributions of effect modifiers and prognostic variables, so unadjusted anchored indirect comparisons can be biased even without individual-level treatment effect heterogeneity.
Random effects meta-analysis of event outcome in the framework of the generalized linear mixed model with applications in sparse data.Statistics in medicine2010; 29(29): 3046–3067
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Transportability of model-based estimands in evidence synthesis
Non-collapsible marginal effect measures depend on joint distributions of effect modifiers and prognostic variables, so unadjusted anchored indirect comparisons can be biased even without individual-level treatment effect heterogeneity.
- Incorporating estimands into meta-analyses of clinical trials