Analysing truncated data with semiparametric transformation models.

Left-truncation often arises when patient information, such as time of diagnosis, is gathered retrospectively. In some cases, the distribution function, sayG(x), of left-truncated variables can be parameterized asG(x; θ), where θ∈Θ⊂Rqand θ is aq-dimensional vector. Under semiparametric transformation models, we demonstrated that the approach of Chenet al.(Semiparametric analysis of transformation models with censored data. Biometrika. 2002;89:659–668) can be used to analyse this type of data. The asymptotic properties of the proposed estimators are derived. A simulation study is conducted to investigate the performance of the proposed estimators. [ABSTRACT FROM AUTHOR]