Analyzing right-censored and length-biased data with varying-coefficient transformation model

Right-censored and length-biased data arise in many applications, including disease screening and epidemiological cohort studies. It is challenging to analyze such data, since independent censoring assumption is violated in the presence of biased sampling. In this paper, we study the varying-coefficient transformation models with right-censored and length-biased data. We use the local linear fitting technique and propose estimators of varying coefficients by constructing the local inverse probability weighted estimating equations. We have shown that the proposed estimators are consistent and asymptotically normal and their variances can be estimated consistently. We pay special attention to the case where the censoring variable depends on the covariates. We conduct simulation studies to assess the performance of the proposed method and demonstrate its application on a real data example.