Conflating marginal and conditional treatment effects: Comments on “Assessing the performance of population adjustment methods for anchored indirect comparisons: A simulation study”
Antonio Remiro‐Azócar, Anna Heath, Gianluca Baio
Abstract
In this commentary, we highlight the importance of: (1) carefully considering and clarifying whether a marginal or conditional treatment effect is of interest in a population-adjusted indirect treatment comparison; and (2) developing distinct methodologies for estimating the different measures of effect. The appropriateness of each methodology depends on the preferred target of inference.
Topics & Concepts
InferenceMarginal structural modelEconometricsMarginal modelPopulationTreatment effectCausal inferenceStatisticsStatistical inferenceComputer scienceMedicineMathematicsArtificial intelligenceRegression analysisTraditional medicineEnvironmental healthAdvanced Causal Inference TechniquesStatistical Methods and Bayesian InferenceHealth Systems, Economic Evaluations, Quality of Life