Search research articles

ABOUT JoVE

Overview Leadership Blog JoVE Help Center

AUTHORS

Publishing Process Editorial Board Scope & Policies Peer Review FAQ Submit

LIBRARIANS

Testimonials Subscriptions Access Resources Library Advisory Board FAQ

RESEARCH

JoVE Journal Methods Collections JoVE Encyclopedia of Experiments Archive

EDUCATION

JoVE Core JoVE Business JoVE Science Education JoVE Lab Manual Faculty Resource Center Faculty Site

Terms & Conditions of Use

Search research articles

Related Experiment Videos

Modeling late entry bias in survival analysis.

Masaaki Matsuura¹, Shinto Eguchi

¹Cancer Institute, Japanese Foundation for Cancer Research, Tokyo 135-8550, Japan. mmatsuura@jfcr.or.jp

|July 14, 2005

Summary

This study addresses challenges in survival analysis with late-entering subjects, often treated as left-truncated data. It introduces a new statistical method to account for potential entry bias in failure time analysis.

Related Concept Videos

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by

Same author

Prediction of cell cycle distribution after drug exposure by high content imaging analysis using low-toxic DNA staining dye.

Pharmacology research & perspectives·2024

Same author

Induction of stearoyl-CoA desaturase confers cell density-dependent ferroptosis resistance in melanoma.

Journal of cellular biochemistry·2024

Same author

Functional evaluation of BRCA1/2 variants of unknown significance with homologous recombination assay and integrative in silico prediction model.

Journal of human genetics·2023

Same author

Polymorphisms of Placental Iodothyronine Deiodinase Genes in a Rural Area of Northern China with High Prevalence of Neural Tube Defects.

Human heredity·2023

Same author

Prognostic implications of prostaglandin E-major urinary metabolite in resected non-small-cell lung cancer.

Interdisciplinary cardiovascular and thoracic surgery·2023

Same author

Risk of low birthweight associated with the timing and frequency of antenatal care visits in Lao PDR: a retrospective cohort study.

BMC pregnancy and childbirth·2023

Area of Science:

Biostatistics
Survival Analysis
Epidemiology

Background:

Failure time analysis often encounters subjects entering the study after its commencement, termed late entries.
Standard statistical methods may treat these late entries as left-truncated data, potentially introducing bias.
Delayed entries might exhibit distinct hazard rates compared to early entrants, necessitating specialized analytical approaches.

Purpose of the Study:

To develop a robust statistical methodology for survival data analysis that explicitly accounts for late entries and potential entry bias.
To construct a flexible model incorporating parameters for delayed entry bias without assuming a specific entry time distribution.
To provide a framework for reliable inference in the presence of non-random entry patterns.

Main Methods:

Development of a statistical model incorporating parameters for delayed entry bias.
Application of likelihood inference to estimate model parameters.
Derivation of the asymptotic behavior of the proposed estimators.
Conducting a simulation study to compare the new method against standard approaches assuming independence of entry and failure times.

Main Results:

The proposed methodology effectively handles late entries in survival data.
Simulation results demonstrate the superiority of the new method over standard approaches when entry bias is present.
The model successfully estimates parameters related to delayed entry bias.

Conclusions:

The developed methodology provides a statistically sound approach for analyzing survival data with late entries and potential entry bias.
This method offers improved accuracy and reliability compared to standard techniques that ignore entry-time dependencies.
The approach is applicable to real-world scenarios, such as mortality analysis in epidemiological studies like that of atomic bomb survivors.

Related Experiment Videos