Current Status Data in the Twenty-First Century: Some Interesting Developments - Interval-Censored-Time-to-Event Data: Methods and Applications - page 83

probability of cure with a semiparametric regression model belonging to the
flexible class of partly linear models for the time to occurrence of the event
and propose sieved likelihood estimation. Ma (2009) has also considered cur-
rent status data in the presence of a cured sub-group assuming that the cure
probability satisfies a generalized linear model with a known link function,
while for susceptible subjects, the event time is modeled using linear or partly
linear Cox models. Likelihood-based strategies are used. An extension, along
very similar lines, to mixed-case interval-censored data is developed in Ma
(2010). An additive risk model for the survival hazard for subjects susceptible
to failure in the current status cure rate model is studied in Ma (2011).
The above survey should give an ample feel for the high level of activity in
the field of current status (and more generally interval-censored) data in recent
times. As I mentioned in the introduction, the goal of the exposition was not to
be exhaustive but to be selective and as was admitted, the selection-bias was
driven to some extent by my personal research interests. A substantial body of
research in this area therefore remains uncovered; some examples include work
on additive hazards regression with current status data initially studied by Lin
et al. (1998) and pursued subsequently by Ghosh (2001) and Martinussen and
Scheike (2002); computational algorithms for interval-censored problems as
developed by Gentlemen and Vandal (2001) and Vandal et al. (2005); infer-
ence for two sample problems with current status data and related models as
developed by Zhang et al. (2001), Zhang (20006), Tong et al. (2007), and most
recently in Groeneboom (2012) using a likelihood-ratio based approach; cur-
rent status data in the context of multistage/multistate models as studied in
Datta and Sundaram (2006) and Lan and Datta (2010); and finally, Bayesian
approaches to the problem where interesting research has been carried out by
D.B. Dunson, Bo Cai, and Lianming Wang, among others.