Marra, G;
Radice, R;
(2020)
Copula Link-Based Additive Models for Right-Censored Event Time Data.
Journal of the American Statistical Association
, 115
(530)
pp. 886-895.
10.1080/01621459.2019.1593178.
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Abstract
This article proposes an approach to estimate and make inference on the parameters of copula link-based survival models. The methodology allows for the margins to be specified using flexible parametric formulations for time-to-event data, the baseline survival functions to be modeled using monotonic splines, and each parameter of the assumed joint survival distribution to depend on an additive predictor incorporating several types of covariate effects. All the model’s coefficients as well as the smoothing parameters associated with the relevant components in the additive predictors are estimated using a carefully structured efficient and stable penalized likelihood algorithm. Some theoretical properties are also discussed. The proposed modeling framework is evaluated in a simulation study and illustrated using a real dataset. The relevant numerical computations can be easily carried out using the freely available GJRM R package. Supplementary materials for this article are available online.
| Type: | Article |
|---|---|
| Title: | Copula Link-Based Additive Models for Right-Censored Event Time Data |
| Open access status: | An open access version is available from UCL Discovery |
| DOI: | 10.1080/01621459.2019.1593178 |
| Publisher version: | https://doi.org/10.1080/01621459.2019.1593178 |
| Language: | English |
| Additional information: | This version is the author accepted manuscript. For information on re-use, please refer to the publisher’s terms and conditions. |
| Keywords: | additive predictor, bivariate survival data, copula, joint model, link function, penalized log-likelihood, regression spline representation, simultaneous parameter estimation |
| UCL classification: | UCL UCL > Provost and Vice Provost Offices > UCL BEAMS UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Maths and Physical Sciences UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Maths and Physical Sciences > Dept of Statistical Science |
| URI: | https://discovery.ucl.ac.uk/id/eprint/10073538 |
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