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Links between analysis of surrogate endpoints and endogeneity
Author(s) -
Ghosh Debashis,
Elliott Michael R.,
Taylor Jeremy M. G.
Publication year - 2010
Publication title -
statistics in medicine
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.996
H-Index - 183
eISSN - 1097-0258
pISSN - 0277-6715
DOI - 10.1002/sim.4027
Subject(s) - endogeneity , covariate , econometrics , estimator , causal inference , instrumental variable , inference , context (archaeology) , computer science , surrogate endpoint , statistics , mathematics , medicine , artificial intelligence , paleontology , biology
There has been substantive interest in the assessment of surrogate endpoints in medical research. These are measures that could potentially replace ‘true’ endpoints in clinical trials and lead to studies that require less follow‐up. Recent research in the area has focused on assessments using causal inference frameworks. Beginning with a simple model for associating the surrogate and true endpoints in the population, we approach the problem as one of endogenous covariates. An instrumental variables estimator and general two‐stage algorithm are proposed. Existing surrogacy frameworks are then evaluated in the context of the model. In addition, we define an extended relative effect estimator as well as a sensitivity analysis for assessing what we term the treatment instrumentality assumption. A numerical example is used to illustrate the methodology. Copyright © 2010 John Wiley & Sons, Ltd.