3 citations · 10 across the 7 of their papers we have counts for
7 papers
Tipping Point Sensitivity Analysis for Missing Data in Time-to-Event Endpoints: Model-Based and Ad hoc Approaches
Ajmal Oodally, Craig Wang, Zheng Li +3
Treatment policy estimands are frequently favored by regulators, as they assess the effect of treatment assignment regardless of post-randomization events. Despite best efforts, mi…
Efficiency of nonparametric superiority tests based on restricted mean survival time versus the log-rank test under proportional hazards
Dominic Magirr, Craig Wang, Xinlei Deng +2
Background: For RCTs with time-to-event endpoints, proportional hazard (PH) models are typically used to estimate treatment effects and logrank tests are commonly used for hypothes…
Image registration based automated lesion correspondence pipeline for longitudinal CT data
Subrata Mukherjee, Thibaud Coroller, Craig Wang +6
Patients diagnosed with metastatic breast cancer (mBC) typically undergo several radiographic assessments during their treatment. mBC often involves multiple metastatic lesions in…
Evaluating causal effects on time-to-event outcomes in an RCT in Oncology with treatment discontinuation
Veronica Ballerini, Björn Bornkamp, Alessandra Mattei +3
In clinical trials, patients may discontinue treatments prematurely, breaking the initial randomization and, thus, challenging inference. Stakeholders in drug development are gener…
Combining Heterogeneous Spatial Datasets with Process-based Spatial Fusion Models: A Unifying Framework
Craig Wang, Reinhard Furrer
In modern spatial statistics, the structure of data that is collected has become more heterogeneous. Depending on the type of spatial data, different modeling strategies for spatia…
EggCounts: a Bayesian hierarchical toolkit to model faecal egg count reductions
Craig Wang, Reinhard Furrer
This is a vignette for the R package eggCounts version 2.0. The package implements a suite of Bayesian hierarchical models dealing with faecal egg count reductions. The models are…
Local-likelihood transformation kernel density estimation for positive random variables
Gery Geenens, Craig Wang
The kernel estimator is known not to be adequate for estimating the density of a positive random variable X. The main reason is the well-known boundary bias problems that it suffer…