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- W2114195038 abstract "Left-truncation often arises when patient information, such as time of diagnosis, is gathered retrospectively. In some cases, the distribution function, say G(x), of left-truncated variables can be parameterized as G(x; θ), where θ∈Θ⊂Rq and θ is a q-dimensional vector. Under semiparametric transformation models, we demonstrated that the approach of Chen et 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." @default.
- W2114195038 created "2016-06-24" @default.
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- W2114195038 date "2013-09-02" @default.
- W2114195038 modified "2023-09-24" @default.
- W2114195038 title "Analysing truncated data with semiparametric transformation models" @default.
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- W2114195038 doi "https://doi.org/10.1080/00949655.2013.831416" @default.
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