ArticlePharmaceutical statistics
The Impact of Model Misspecification on the Individual Causal Association in Surrogate Endpoint Evaluation.
Article in Pharmaceutical statistics. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Authors and funding
5 authors.
Funding
Abstract
Surrogate endpoints are often used in place of expensive, delayed, or rare clinical endpoints in clinical trials. However, regulatory authorities require thorough evaluation to accept these surrogate endpoints as reliable substitutes. One evaluation approach is the information-theoretic causal inference framework, which quantifies surrogacy using the individual causal association (ICA). Like most causal inference methods, this approach relies on models that are only partially identifiable. For continuous outcomes, a normal model is often used. In this study, we explored the effects of model misspecification across various scenarios. We first considered true data-generating mechanisms based on multivariate
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