Conditional Score Approach to Errors-in-Variable Current Status Data Under the Proportional Odds Model

摘要

The conditional score approach is proposed to the analysis of errors-in-varlable current status data under the proportional odds model. Distinct from the conditional (cores in other applications, the proposed conditional score involves a high-dimensional nuisaace parameter, causing challenges in both asymptotic theory and computation. We propose a composite algorithm combining the Newton-Raphson and self-consistency algorithms for computation and develop an efficient conditional score, analogous to the efficient score from a typical semiparametric likelihood, for building an asymptotic linear expression and hence the asymptotic distribution of the conditional-score estimator for the regression parameter. Our proposal is shown to perform well In simulation studies and is applied to a zebrafish basal cell carcinoma data involving measurement errors in gene expression levels.