REGRESSION ANALYSIS OF CASE II INTERVAL-CENSORED FAILURE TIME DATA WITH THE ADDITIVE HAZARDS MODEL.

Interval-censored failure time data often arise in clinical trials and medical follow-up studies, and a few methods have been proposed for their regression analysis using various regression models (Finkelstein (1986); Huang (1996); Lin, Oakes, and Ying (1998); Sun (2006)). This paper proposes an estimating equation-based approach for regression analysis of interval-censored failure time data with the additive hazards model. The proposed approach is robust and applies to both noninformative and informative censoring cases. A major advantage of the proposed method is that it does not involve estimation of any baseline hazard function. The implementation of the propsoed approach is easy and fast. Asymptotic properties of the proposed estimates are established and some simulation results and an application are provided.

[1]  Donglin Zeng,et al.  Semiparametric additive risks model for interval-censored data , 2006 .

[2]  Jong S. Kim,et al.  EFFICIENT ESTIMATION FOR THE PROPORTIONAL HAZARDS MODEL WITH LEFT-TRUNCATED AND "CASE 1" INTERVAL-CENSORED DATA , 2003 .

[3]  Alan J. Lee,et al.  U-Statistics: Theory and Practice , 1990 .

[4]  D. Finkelstein,et al.  A proportional hazards model for interval-censored failure time data. , 1986, Biometrics.

[5]  John D. Kalbfleisch,et al.  The Statistical Analysis of Failure Data , 1986, IEEE Transactions on Reliability.

[6]  Torben Martinussen,et al.  Efficient estimation in additive hazards regression with current status data , 2002 .

[7]  Xuewen Lu,et al.  On efficient estimation in additive hazards regression with current status data , 2012, Comput. Stat. Data Anal..

[8]  L. J. Wei,et al.  Regression analysis of multivariate incomplete failure time data by modeling marginal distributions , 1989 .

[9]  Zhiliang Ying,et al.  Additive hazards regression with current status data , 1998 .

[10]  D. Lin,et al.  Cox regression analysis of multivariate failure time data: the marginal approach. , 1994, Statistics in medicine.

[11]  Zhigang Zhang,et al.  Statistical analysis of current status data with informative observation times , 2005, Statistics in medicine.

[12]  Anastasios A. Tsiatis,et al.  Computationally simple accelerated failure time regression for interval censored data , 2001 .

[13]  A. V. Peterson,et al.  On the regression analysis of multivariate failure time data , 1981 .

[14]  P J Kelly,et al.  Survival analysis for recurrent event data: an application to childhood infectious diseases. , 2000, Statistics in medicine.

[15]  Zhiliang Ying,et al.  Marginal proportional hazards models for multiple event‐time data , 2001 .