Continuous covariate frailty models for censored and truncated clustered data

DOI10.1016/j.jspi.2012.02.044zbMath1237.62133OpenAlexW1984548453WikidataQ61849246 ScholiaQ61849246MaRDI QIDQ419302

Paul Janssen, Ricardo Cao, Ignacio López-de-Ullibarri

Publication date: 18 May 2012

Published in: Journal of Statistical Planning and Inference (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.jspi.2012.02.044

zbMATH Keywords

kernel estimationconditional hazard functionsclustered survival dataestimation via transformations

Mathematics Subject Classification ID

Applications of statistics to biology and medical sciences; meta analysis (62P10) Censored data models (62N01) Monte Carlo methods (65C05) Estimation in survival analysis and censored data (62N02)

Related Items (3)

Testing for decreasing heterogeneity in a new time-varying frailty model ⋮ Goodness‐of‐fit tests in proportional hazards models with random effects ⋮ Composite empirical likelihood for multisample clustered data

Uses Software

• S-PLUS
• MEMSS

Cites Work

• The frailty model.
• Fitting Conditional Survival Models to Meta‐Analytic Data by Using a Transformation Toward Mixed‐Effects Models
• Strong representation of a generalized product-limit estimator for truncated and censored data with some applications
• Mixed-Effects Models in S and S-PLUS
• Analysis of Covariance with Incomplete Data Via Semiparametric Model Transformations

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