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.
Towards causally interpretable meta-analysis: transporting inferences from multiple randomized trials to a new target population.Epidemiology (Cambridge, Mass.) 2020; 31(3): 334
1 Pith paper cite this work. Polarity classification is still indexing.
1
Pith paper citing it
fields
stat.ME 1years
2022 1verdicts
UNVERDICTED 1representative citing papers
citing papers explorer
-
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.