On the conditional probability for assessing time dependence of association in shared frailty models with bivariate current status data

DOI10.1016/j.jspi.2016.09.009zbMath1394.62134OpenAlexW2535032784MaRDI QIDQ729712

Steffen Unkel

Publication date: 22 December 2016

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.2016.09.009

zbMATH Keywords

heterogeneityconditional probabilityfrailty modelscurrent status datacross-sectional datatime-varying association

Mathematics Subject Classification ID

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

Uses Software

• invGauss

Cites Work

• Unnamed Item
• Survival and event history analysis. A process point of view
• Analysis of multivariate survival data
• The frailty model.
• The statistical analysis of interval-censored failure time data.
• On assessing the association for bivariate current status data
• Bivariate current status data with univariate monitoring times
• Bivariate Survival Models Induced by Frailties
• Outliers in Circular Data
• Time-Dependent Association Measures for Bivariate Survival Distributions
• A model for association in bivariate life tables and its application in epidemiological studies of familial tendency in chronic disease incidence
• Testing Independence for Bivariate Current Status Data
• The relative frailty variance and shared frailty models
• A NEW MEASURE OF RANK CORRELATION
• Diagnostic plots for assessing the frailty distribution in multivariate survival data

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