Elastic integrative analysis of randomised trial and real-world data for treatment heterogeneity estimation.
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ABSTRACT: We propose a test-based elastic integrative analysis of the randomised trial and real-world data to estimate treatment effect heterogeneity with a vector of known effect modifiers. When the real-world data are not subject to bias, our approach combines the trial and real-world data for efficient estimation. Utilising the trial design, we construct a test to decide whether or not to use real-world data. We characterise the asymptotic distribution of the test-based estimator under local alternatives. We provide a data-adaptive procedure to select the test threshold that promises the smallest mean square error and an elastic confidence interval with a good finite-sample coverage property.
SUBMITTER: Yang S
PROVIDER: S-EPMC10376438 | biostudies-literature | 2023 Jul
REPOSITORIES: biostudies-literature
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