3 citations · 4 across the 4 of their papers we have counts for
4 papers
A Graphical Approach to Treatment Effect Estimation with Observational Network Data
Meta-Lina Spohn, Leonard Henckel, Marloes H. Maathuis
We propose an easy-to-use adjustment estimator for the effect of a treatment based on observational data from a single (social) network of units. The approach allows for interactio…
Treatment Effect Estimation with Observational Network Data using Machine Learning
Corinne Emmenegger, Meta-Lina Spohn, Timon Elmer +1
Causal inference methods for treatment effect estimation usually assume independent units. However, this assumption is often questionable because units may interact, resulting in s…
PKLM: A flexible MCAR test using Classification
Meta-Lina Spohn, Jeffrey Näf, Loris Michel +1
We develop a fully non-parametric, easy-to-use, and powerful test for the missing completely at random (MCAR) assumption on the missingness mechanism of a dataset. The test compare…
Imputation Scores
Jeffrey Näf, Meta-Lina Spohn, Loris Michel +1
Given the prevalence of missing data in modern statistical research, a broad range of methods is available for any given imputation task. How does one choose the `best' imputation…