Comparison of variance estimation methods in semiparametric accelerated failure time models for multivariate failure time data
DOI10.1007/s42081-021-00126-yzbMath1478.62302OpenAlexW3176119392MaRDI QIDQ2068964
Kyuhyun Kim, Sangwook Kang, Jungyeol Ko
Publication date: 20 January 2022
Published in: Japanese Journal of Statistics and Data Science (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1007/s42081-021-00126-y
resamplingiterative methodssandwich variance estimatormultiplier bootstrapinduced smoothingrank-based estimation
Computational methods for problems pertaining to statistics (62-08) Estimation in multivariate analysis (62H12) Applications of statistics to biology and medical sciences; meta analysis (62P10) Nonparametric estimation (62G05) Estimation in survival analysis and censored data (62N02) Reliability and life testing (62N05)
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- Fast accelerated failure time modeling for case-cohort data
- Marginal semiparametric multivariate accelerated failure time model with generalized estimating equations
- An introduction to copulas.
- Rank regression for accelerated failure time model with clustered and censored data
- Monotone estimating equations for censored data
- A class of rank test procedures for censored survival data
- Induced smoothing for the semiparametric accelerated failure time model: asymptotics and extensions to clustered data
- Rank Regression Analysis of Multivariate Failure Time Data Based on Marginal Linear Models
- Efficient resampling methods for nonsmooth estimating functions
- Linear rank tests with right censored data
- Rank-based inference for the accelerated failure time model
- Standard errors and covariance matrices for smoothed rank estimators
- A generalized Wilcoxon test for comparing arbitrarily singly-censored samples
- Semiparametric Accelerated Failure Time Modeling for Clustered Failure Times From Stratified Sampling
