Semiparametric regression on cumulative incidence function with interval-censored competing risks data and missing event types

Cumulative incidence in competing risks data and competing risks regression analysis.

Competing risks occur commonly in medical research. For example, both treatment-related mortality and disease recurrence are important outcomes of interest and well-known competing risks in cancer research. In the analysis of competing risks data, methods of standard survival analysis such as the Kaplan-Meier method for estimation of cumulative incidence, the log-rank test for comparison of cum...

Semiparametric analysis of mixture regression models with competing risks data.

In the analysis of competing risks data, cumulative incidence function is a useful summary of the overall crude risk for a failure type of interest. Mixture regression modeling has served as a natural approach to performing covariate analysis based on this quantity. However, existing mixture regression methods with competing risks data either impose parametric assumptions on the conditional ris...

Semiparametric Additive Risks Model for Interval-censored Data

Interval-censored event time data often arise in medical and public health studies. In such a setting, the exact time of the event of interest cannot be observed and is only known to fall between two monitoring times. Our interest focuses on the estimation of the effect of risk factors on interval-censored data under the semiparametric additive hazards model. A nonparametric step-function is us...

Semiparametric Regression Analysis of Bivariate Interval-Censored Data

Survival analysis is a long-lasting and popular research area and has numerous applications in all fields such as social science, engineering, economics, industry, and public health. Interval-censored data are a special type of survival data, in which the survival time of interest is never exactly observed but is known to fall within some observed interval. Interval-censored data arise commonly...

Analysis of Partly Interval-Censored Data under Competing Risks Framework