2 citations · 3 across the 3 of their papers we have counts for
3 papers
CoBWeb: a user-friendly web application to estimate causal treatment effects from observational data using multiple algorithms
Andreas Markoulidakis, Peter Holmans, Philip Pallmann +2
Background/aims: While randomized controlled trials are the gold standard for measuring causal effects, robust conclusions about causal relationships can be obtained using data fro…
How balance and sample size impact bias in the estimation of causal treatment effects: A simulation study
Andreas Markoulidakis, Peter Holmans, Philip Pallmann +2
Observational studies are often used to understand relationships between exposures and outcomes. They do not, however, allow conclusions about causal relationships to be drawn unle…
A tutorial comparing different covariate balancing methods with an application evaluating the causal effects of substance use treatment programs for adolescents
Andreas Markoulidakis, Khadijeh Taiyari, Peter Holmans +4
Randomized controlled trials are the gold standard for measuring causal effects. However, they are often not always feasible, and causal treatment effects must be estimated from ob…