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.
Accounting for misclassified outcomes in binary regression models using multiple imputation with internal validation data
1 Pith paper cite this work. Polarity classification is still indexing.
1
Pith paper citing it
fields
stat.ME 1years
2026 1verdicts
UNVERDICTED 1representative citing papers
citing papers explorer
-
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.