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


Yi-Hau Chen, Institute of Statistical Science, Academia Sinica, No. 128 Sec. 2 Academia Road, Taipei 11529, Taiwan.


Abstract.  The conditional score approach is proposed to the analysis of errors-in-variable current status data under the proportional odds model. Distinct from the conditional scores in other applications, the proposed conditional score involves a high-dimensional nuisance 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.

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