A flexible Bayesian non-parametric approach for fitting the odds to case II interval-censored data. Issue 16 (2nd November 2018)
- Record Type:
- Journal Article
- Title:
- A flexible Bayesian non-parametric approach for fitting the odds to case II interval-censored data. Issue 16 (2nd November 2018)
- Main Title:
- A flexible Bayesian non-parametric approach for fitting the odds to case II interval-censored data
- Authors:
- Wu, Yuh-Jenn
Fang, Wei-Quan
Cheng, Li-Hsueh
Chu, Kai-Chi
Shih, Yin-Tzer
Chien, Li-Chu - Abstract:
- Abstract: Interval-censored survival data arise often in medical applications and clinical trials [Wang L, Sun J, Tong X. Regression analyis of case II interval-censored failure time data with the additive hazards model. Statistica Sinica. 2010;20:1709–1723]. However, most of existing interval-censored survival analysis techniques suffer from challenges such as heavy computational cost or non-proportionality of hazard rates due to complicated data structure [Wang L, Lin X. A Bayesian approach for analyzing case 2 interval-censored data under the semiparametric proportional odds model. Statistics & Probability Letters. 2011;81:876–883; Banerjee T, Chen M-H, Dey DK, et al. Bayesian analysis of generalized odds-rate hazards models for survival data. Lifetime Data Analysis. 2007;13:241–260]. To address these challenges, in this paper, we introduce a flexible Bayesian non-parametric procedure for the estimation of the odds under interval censoring, case II. We use Bernstein polynomials to introduce a prior for modeling the odds and propose a novel and easy-to-implement sampling manner based on the Markov chain Monte Carlo algorithms to study the posterior distributions. We also give general results on asymptotic properties of the posterior distributions. The simulated examples show that the proposed approach is quite satisfactory in the cases considered. The use of the proposed method is further illustrated by analyzing the hemophilia study data [McMahan CS, Wang L. A package forAbstract: Interval-censored survival data arise often in medical applications and clinical trials [Wang L, Sun J, Tong X. Regression analyis of case II interval-censored failure time data with the additive hazards model. Statistica Sinica. 2010;20:1709–1723]. However, most of existing interval-censored survival analysis techniques suffer from challenges such as heavy computational cost or non-proportionality of hazard rates due to complicated data structure [Wang L, Lin X. A Bayesian approach for analyzing case 2 interval-censored data under the semiparametric proportional odds model. Statistics & Probability Letters. 2011;81:876–883; Banerjee T, Chen M-H, Dey DK, et al. Bayesian analysis of generalized odds-rate hazards models for survival data. Lifetime Data Analysis. 2007;13:241–260]. To address these challenges, in this paper, we introduce a flexible Bayesian non-parametric procedure for the estimation of the odds under interval censoring, case II. We use Bernstein polynomials to introduce a prior for modeling the odds and propose a novel and easy-to-implement sampling manner based on the Markov chain Monte Carlo algorithms to study the posterior distributions. We also give general results on asymptotic properties of the posterior distributions. The simulated examples show that the proposed approach is quite satisfactory in the cases considered. The use of the proposed method is further illustrated by analyzing the hemophilia study data [McMahan CS, Wang L. A package for semiparametric regression analysis of interval-censored data; 2015.http://CRAN.R-project.org/package=ICsurv . … (more)
- Is Part Of:
- Journal of statistical computation and simulation. Volume 88:Issue 16(2018)
- Journal:
- Journal of statistical computation and simulation
- Issue:
- Volume 88:Issue 16(2018)
- Issue Display:
- Volume 88, Issue 16 (2018)
- Year:
- 2018
- Volume:
- 88
- Issue:
- 16
- Issue Sort Value:
- 2018-0088-0016-0000
- Page Start:
- 3132
- Page End:
- 3150
- Publication Date:
- 2018-11-02
- Subjects:
- Case II interval-censored data -- odds -- Bernstein polynomials -- Markov chain Monte Carlo
62N01 -- 62F15
Mathematical statistics -- Data processing -- Periodicals
Digital computer simulation -- Periodicals
519.5028505 - Journal URLs:
- http://www.tandfonline.com/loi/gscs20 ↗
http://www.tandfonline.com/ ↗ - DOI:
- 10.1080/00949655.2018.1504944 ↗
- Languages:
- English
- ISSNs:
- 0094-9655
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library DSC - 5066.820000
British Library DSC - BLDSS-3PM
British Library HMNTS - ELD Digital store - Ingest File:
- 7187.xml