5 papers · 1 filter
Deriving Complete Constraints in Hidden Variable Models
Michael C. Sachs, Erin E. Gabriel, Robin J. Evans +1
Hidden variable graphical models can sometimes imply constraints on the observable distribution that are more complex than simple conditional independence relations. These observab…
Definition, Identification, and Estimation of the Direct and Indirect Number Needed to Treat
Valentin Vancak, Arvid Sjölander
The number needed to treat (NNT) is an efficacy and effect size measure commonly used in epidemiological studies and meta-analyses. The NNT was originally defined as the average nu…
Nonparametric Bounds for Evaluating the Clinical Utility of Treatment Rules
Johannes Hruza, Erin Gabriel, Arvid Sjölander +2
Evaluating the value of new clinical treatment rules based on patient characteristics is important but often complicated by hidden confounding factors in observational studies. Sta…
On the limitations for causal inference in Cox models with time-varying treatment
Mark B. Knudsen, Erin E. Gabriel, Torben Martinussen +2
When using the Cox model to analyze the effect of a time-varying treatment on a survival outcome, treatment is commonly included, using only the current level as a time-dependent c…
Estimation of the Number Needed to Treat, the Number Needed to be Exposed, and the Exposure Impact Number with Instrumental Variables
Valentin Vancak, Arvid Sjölander
The Number needed to treat (NNT) is an efficacy index defined as the average number of patients needed to treat to attain one additional treatment benefit. In observational studies…