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Literature DB >> 27086362

Nonparametric and semiparametric regression estimation for length-biased survival data.

Abstract

For the past several decades, nonparametric and semiparametric modeling for conventional right-censored survival data has been investigated intensively under a noninformative censoring mechanism. However, these methods may not be applicable for analyzing right-censored survival data that arise from prevalent cohorts when the failure times are subject to length-biased sampling. This review article is intended to provide a summary of some newly developed methods as well as established methods for analyzing length-biased data.

Entities: Chemical Disease Gene Species

Keywords: Estimating equation; Left truncation; Length-biased sampling; Likelihood; Nonparametric estimator; Semiparametric models

Mesh：

Year: 2016 PMID： 27086362 PMCID： PMC5065937 DOI： 10.1007/s10985-016-9367-y

Source DB: PubMed Journal: Lifetime Data Anal ISSN： 1380-7870 Impact factor: 1.588

32 in total

Nonparametric and semiparametric regression estimation for length-biased survival data.

1. Pseudo-partial likelihood for proportional hazards models with biased-sampling data.

2. Nonparametric tests for right-censored data with biased sampling.

3. Score Estimating Equations from Embedded Likelihood Functions under Accelerated Failure Time Model.

4. Proportional hazards model with varying coefficients for length-biased data.

5. Combined estimating equation approaches for semiparametric transformation models with length-biased survival data.

6. Imputation for semiparametric transformation models with biased-sampling data.

7. Semiparametric regression in size-biased sampling.

8. A Unified Approach to Semiparametric Transformation Models under General Biased Sampling Schemes.

9. Statistical models for prevalent cohort data.

10. Statistical methods for analyzing right-censored length-biased data under cox model.

1. Conditional Independence Test of Failure and Truncation Times: Essential Tool for Method Selection.

2. A risk set adjustment for proportional hazards modeling of combined cohort data.

3. A pairwise likelihood augmented Cox estimator for left-truncated data.