Modern approaches for evaluating treatment effect heterogeneity from clinical trials and observational data
I Lipkovich, D Svensson, B Ratitch… - Statistics in …, 2024 - Wiley Online Library
In this paper, we review recent advances in statistical methods for the evaluation of the
heterogeneity of treatment effects (HTE), including subgroup identification and estimation of …
heterogeneity of treatment effects (HTE), including subgroup identification and estimation of …
Learning optimal group-structured individualized treatment rules with many treatments
Data driven individualized decision making problems have received a lot of attentions in
recent years. In particular, decision makers aim to determine the optimal Individualized …
recent years. In particular, decision makers aim to determine the optimal Individualized …
Learning optimal distributionally robust individualized treatment rules
W Mo, Z Qi, Y Liu - Journal of the American Statistical Association, 2021 - Taylor & Francis
Recent development in the data-driven decision science has seen great advances in
individualized decision making. Given data with individual covariates, treatment …
individualized decision making. Given data with individual covariates, treatment …
Learning individualized treatment rules with many treatments: A supervised clustering approach using adaptive fusion
Abstract Learning an optimal Individualized Treatment Rule (ITR) is a very important
problem in precision medicine. This paper is concerned with the challenge when the …
problem in precision medicine. This paper is concerned with the challenge when the …
[BOOK][B] Real world health care data analysis: causal methods and implementation using SAS
Discover best practices for real world data research with SAS code and examples Real
world health care data is common and growing in use with sources such as observational …
world health care data is common and growing in use with sources such as observational …
Efficient learning of optimal individualized treatment rules for heteroscedastic or misspecified treatment-free effect models
W Mo, Y Liu - Journal of the Royal Statistical Society Series B …, 2022 - academic.oup.com
Recent development in data-driven decision science has seen great advances in
individualized decision making. Given data with individual covariates, treatment …
individualized decision making. Given data with individual covariates, treatment …
Optimal individualized treatment rule for combination treatments under budget constraints
The individualized treatment rule (ITR), which recommends an optimal treatment based on
individual characteristics, has drawn considerable interest from many areas such as …
individual characteristics, has drawn considerable interest from many areas such as …
Multi-label residual weighted learning for individualized combination treatment rule
Individualized treatment rules (ITRs) have been widely applied in many fields such as
precision medicine and personalized marketing. Beyond the extensive studies on ITR for …
precision medicine and personalized marketing. Beyond the extensive studies on ITR for …
Estimating individualized optimal combination therapies through outcome weighted deep learning algorithms
With the advancement in drug development, multiple treatments are available for a single
disease. Patients can often benefit from taking multiple treatments simultaneously. For …
disease. Patients can often benefit from taking multiple treatments simultaneously. For …
Multicategory angle-based learning for estimating optimal dynamic treatment regimes with censored data
An optimal dynamic treatment regime (DTR) consists of a sequence of decision rules in
maximizing long-term benefits, which is applicable for chronic diseases such as HIV …
maximizing long-term benefits, which is applicable for chronic diseases such as HIV …