Dynamic Treatment Regimes: Statistical Methods for Precision Medicine provides a
comprehensive introduction to statistical methodology for the evaluation and discovery of …

Precision medicine is a medical paradigm that focuses on finding the most effective
treatment decision based on individual patient information. For many complex diseases …

We propose a test-based elastic integrative analysis of the randomised trial and real-world
data to estimate treatment effect heterogeneity with a vector of known effect modifiers. When …

Recent development in statistical methodology for personalized treatment decision has
utilized high-dimensional regression to take into account a large number of patients' …

A plethora of disparate statistical methods have been proposed for subgroup identification to
help tailor treatment decisions for patients. However a majority of them do not have …

We propose a multithreshold change plane regression model which naturally partitions the
observed subjects into subgroups with different covariate effects. The underlying grouping …

Recent advances in dynamic treatment regimes (DTRs) provide powerful optimal treatment
searching algorithms, which are tailored to individuals' specific needs and able to maximize …

Inferring the heterogeneous treatment effect is a fundamental problem in many applications.
In this paper, we focus on estimating the Conditional Average Treatment Effect (CATE), that …

We consider a single‐index regression model, uniquely constrained to estimate interactions
between a set of pretreatment covariates and a treatment variable on their effects on a …

We propose a novel two‐stage procedure for change point detection and parameter
estimation in a multi‐threshold proportional hazards model. In the first stage, we estimate the …