932 citations · 1.4k across the 10 of their papers we have counts for
12 papers
Simulation Experiments as a Causal Problem
Tyrel Stokes, Ian Shrier, Russell Steele
Simulation methods are among the most ubiquitous methodological tools in statistical science. In particular, statisticians often is simulation to explore properties of statistical…
metamedian: An R package for meta-analyzing studies reporting medians
Sean McGrath, XiaoFei Zhao, Omer Ozturk +3
When performing an aggregate data meta-analysis of a continuous outcome, researchers often come across primary studies that report the sample median of the outcome. However, standa…
Standard error estimation in meta-analysis of studies reporting medians
Sean McGrath, Stephan Katzenschlager, Alexandra J. Zimmer +3
We consider the setting of an aggregate data meta-analysis of a continuous outcome of interest. When the distribution of the outcome is skewed, it is often the case that some prima…
Injury risk increases minimally over a large range of changes in activity level in children
Chinchin Wang, Tyrel Stokes, jorge Trejo Vargas +3
Background: Limited research exists on the association between changes in physical activity levels and injury in children. Objective: To assess how well different variations of the…
Implementing multiple imputation for missing data in longitudinal studies when models are not feasible: A tutorial on the random hot deck approach
Chinchin Wang, Tyrel Stokes, Russell Steele +2
Objective: Researchers often use model-based multiple imputation to handle missing at random data to minimize bias while making the best use of all available data. However, there a…
Causal Simulation Experiments: Lessons from Bias Amplification
Tyrel Stokes, Russell Steele, Ian Shrier
Recent theoretical work in causal inference has explored an important class of variables which, when conditioned on, may further amplify existing unmeasured confounding bias (bias…