Reducing sample size needed for accelerated failure time model using more efficient sampling methods

DOI10.1080/15598608.2018.1431574zbMath1426.62303OpenAlexW2791321044MaRDI QIDQ2321822

Hani M. Samawi, Jingjing Yin, Lili Yu, Amal Helu, Haresh D. Rochani, Robert L. Vogel

Publication date: 23 August 2019

Published in: Journal of Statistical Theory and Practice (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1080/15598608.2018.1431574

zbMATH Keywords

survival analysisaccelerated failure time modelextreme ranked set samplingmoving extreme ranked set samplinghazards ratio

Mathematics Subject Classification ID

Applications of statistics to biology and medical sciences; meta analysis (62P10) Sampling theory, sample surveys (62D05) Reliability and life testing (62N05)

Related Items (7)

On Improving the Performance of Logistic Regression Analysis Via Extreme Ranking ⋮ Reducing sample size needed for cox-proportional hazards model analysis using more efficient sampling method ⋮ A ranked-based estimator of the mean past lifetime with an application ⋮ Discrete-time survival analysis under ranked set sampling: an application to Turkish motor insurance data ⋮ Efficient estimation of cumulative distribution function using moving extreme ranked set sampling with application to reliability ⋮ Proportional hazards model under ranked set sampling scheme using censored data of coronary heart disease ⋮ Further improving the performance of logistic regression analysis using double extreme ranking

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• On Bivariate Ranked Set Sampling for Distribution and Quantile Estimation and Quantile Interval Estimation Using Ratio Estimator
• Estimating the Population Mean Using Extreme Ranked Set Sampling
• Survival Analysis

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