220 citations · 782 across the 19 of their papers we have counts for
19 papers
Do we become wiser with time? On causal equivalence with tiered background knowledge
Christine W. Bang, Vanessa Didelez
Equivalence classes of DAGs (represented by CPDAGs) may be too large to provide useful causal information. Here, we address incorporating tiered background knowledge yielding restr…
Variable selection in linear regression models: choosing the best subset is not always the best choice
Moritz Hanke, Louis Dijkstra, Ronja Foraita +1
Variable selection in linear regression settings is a much discussed problem. Best subset selection (BSS) is often considered the intuitive 'gold standard', with its use being rest…
Graphical criteria for the identification of marginal causal effects in continuous-time survival and event-history analyses
Kjetil Røysland, Pål Ryalen, Mari Nygård +1
We consider continuous-time survival or more general event-history settings, where the aim is to infer the causal effect of a time-dependent treatment process. This is formalised a…
Parameterizing and Simulating from Causal Models
Robin J. Evans, Vanessa Didelez
Many statistical problems in causal inference involve a probability distribution other than the one from which data are actually observed; as an additional complication, the object…
Multiple imputation and test-wise deletion for causal discovery with incomplete cohort data
Janine Witte, Ronja Foraita, Vanessa Didelez
Causal discovery algorithms estimate causal graphs from observational data. This can provide a valuable complement to analyses focussing on the causal relation between individual t…
A practical guide to causal discovery with cohort data
Ryan M. Andrews, Ronja Foraita, Vanessa Didelez +1
In this guide, we present how to perform constraint-based causal discovery using three popular software packages: pcalg (with add-ons tpc and micd), bnlearn, and TETRAD. We focus o…