Regression analysis of bivariate current status data under the gamma-frailty proportional hazards model using the EM algorithm

DOI10.1016/j.csda.2014.10.013OpenAlexW2077490998MaRDI QIDQ1623788

Naichen Wang, Christopher S. McMahan, Lianming Wang

Publication date: 23 November 2018

Published in: Computational Statistics and Data Analysis (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.csda.2014.10.013

zbMATH Keywords

EM algorithmproportional hazards modelfrailty modelmultivariate regressioncurrent status datamonotone splinesPoisson latent variables

Mathematics Subject Classification ID

Computational methods for problems pertaining to statistics (62-08) Applications of statistics to biology and medical sciences; meta analysis (62P10) Censored data models (62N01) Estimation in survival analysis and censored data (62N02)

Related Items

Variable selection for generalized odds rate mixture cure models with interval-censored failure time data, Regression analysis of current status data in the presence of dependent censoring with applications to tumorigenicity experiments, Maximum likelihood estimation and expectation-maximization algorithm for controlled branching processes, Estimation of the additive hazards model with linear inequality restrictions based on current status data, An extended proportional hazards model for interval-censored data subject to instantaneous failures, Copula link-based additive models for bivariate time-to-event outcomes with general censoring scheme, A new approach for regression analysis of multivariate current status data with informative censoring, A flexible parametric approach for analyzing arbitrarily censored data that are potentially subject to left truncation under the proportional hazards model, Goodness-of-fit inference for the additive hazards regression model with clustered current status data, A Gamma-frailty proportional hazards model for bivariate interval-censored data, Semiparametric regression analysis of multivariate doubly censored data, A vine copula approach for regression analysis of bivariate current status data with informative censoring, Semiparametric probit models with univariate and bivariate current-status data

Uses Software

• bayesSurv

Cites Work

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