A new semiparametric estimator for misclassified competing risks data that uses external validation probabilities and B-spline sieve pseudo-likelihood, shown to be consistent with better efficiency than prior methods in simulations and an HIV application.
The effects of misclassification on the estimation of relative risk
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Semiparametric Regression for Misclassified Competing Risks Data
A new semiparametric estimator for misclassified competing risks data that uses external validation probabilities and B-spline sieve pseudo-likelihood, shown to be consistent with better efficiency than prior methods in simulations and an HIV application.