5 citations · 33 across the 19 of their papers we have counts for
11 papers · 1 filter
Adaptive sparsening and smoothing of the treatment model for longitudinal causal inference using outcome-adaptive LASSO and marginal fused LASSO
Mireille E Schnitzer, Denis Talbot, Yan Liu +5
Causal variable selection in time-varying treatment settings is challenging due to evolving confounding effects. Existing methods mainly focus on time-fixed exposures and are not d…
Robust integration of external control data in randomized trials
Rickard Karlsson, Guanbo Wang, Piersilvio De Bartolomeis +2
One approach for increasing the efficiency of randomized trials is the use of "external controls" -- individuals who received the control treatment studied in the trial during rout…
Identification strategies for combining an experimental study with external data
Lawson Ung, Guanbo Wang, Sebastien Haneuse +2
There is increasing interest in combining information from experimental studies, including randomized and single-group trials, with information from external experimental or observ…
Extending Inferences from Randomized Clinical Trials to Target Populations: A Scoping Review of Transportability Methods
Guanbo Wang, Ting-Wei Ernie Liao, David Furfaro +2
Objective: Randomized controlled trial (RCT) results often inform clinical decision-making, but the highly curated populations of trials and the care provided during the trial are…
Association between Sitting Time and Urinary Incontinence in the US Population: data from the National Health and Nutrition Examination Survey (NHANES) 2007 to 2018
Guanbo Wang, Xingpeng Di
Background Urinary incontinence (UI) is a common health problem that affects the life and health quality of millions of people in the US. We aimed to investigate the association be…
Efficient estimation of subgroup treatment effects using multi-source data
Guanbo Wang, Alexander Levis, Jon Steingrimsson +1
Investigators often use multi-source data (e.g., multi-center trials, meta-analyses of randomized trials, pooled analyses of observational cohorts) to learn about the effects of in…
CausalMetaR: An R package for performing causally interpretable meta-analyses
Guanbo Wang, Sean McGrath, Yi Lian
Researchers would often like to leverage data from a collection of sources (e.g., primary studies in a meta-analysis) to estimate causal effects in a target population of interest.…
Causal inference under transportability assumptions for conditional relative effect measures
Guanbo Wang, Alexander Levis, Jon Steingrimsson +1
When extending inferences from a randomized trial to a new target population, the transportability condition for conditional difference effect measures is invoked to identify the m…
Penalized G-estimation for effect modifier selection in a structural nested mean model for repeated outcomes
Ajmery Jaman, Guanbo Wang, Ashkan Ertefaie +4
Effect modification occurs when the impact of the treatment on an outcome varies based on the levels of other covariates known as effect modifiers. Modeling these effect difference…
Continuous-time structural failure time model for intermittent treatment
Guanbo Wang, Siyi Liu, Shu Yang
The intermittent intake of treatment is commonly seen in patients with chronic disease. For example, patients with atrial fibrillation may need to discontinue the oral anticoagulan…
Non-collapsibility and Built-in Selection Bias of Hazard Ratio in Randomized Controlled Trials
Helen Bian, Menglan Pang, Guanbo Wang +1
Background: The hazard ratio of the Cox proportional hazards model is widely used in randomized controlled trials to assess treatment effects. However, two properties of the hazard…