34 citations · 47 across the 9 of their papers we have counts for
10 papers
A causal modeling perspective on decision theory
Arvid Sjölander
Decision theory provides a formal framework for how agents should make choices under uncertainty, drawing on ideas from philosophy, probability, and causality. Despite significant…
The impact of coarsening an exposure on partial identifiability in instrumental variable settings
Erin E. Gabriel, Michael C. Sachs, Arvid Sjölander
In instrumental variable (IV) settings, such as in imperfect randomized trials and observational studies with Mendelian randomization, one may encounter a continuous exposure, the…
Propensity weighting plus adjustment in proportional hazards model is not doubly robust
Erin E Gabriel, Michael C Sachs, Ingeborg Waernbaum +5
Recently, it has become common for applied works to combine commonly used survival analysis modeling methods, such as the multivariable Cox model and propensity score weighting, wi…
Inverse probability of treatment weighting with generalized linear outcome models for doubly robust estimation
Erin E Gabriel, Michael C Sachs, Torben Martinussen +4
There are now many options for doubly robust estimation; however, there is a concerning trend in the applied literature to believe that the combination of a propensity score and an…
Sharp nonparametric bounds for decomposition effects with two binary mediators
Erin E Gabriel, Michael C Sachs, Arvid Sjölander
In randomized trials, once the total effect of the intervention has been estimated, it is often of interest to explore mechanistic effects through mediators along the causal pathwa…
Sharp Lower and Upper Bounds for the Covariance of Bounded Random Variables
Ola Hössjer, Arvid Sjölander
In this paper we derive sharp lower and upper bounds for the covariance of two bounded random variables when knowledge about their expected values, variances or both is available.…
Nonparametric bounds for causal effects in imperfect randomized experiments
Erin E. Gabriel, Arvid Sjölander, Michael C. Sachs
Nonignorable missingness and noncompliance can occur even in well-designed randomized experiments making the intervention effect that the experiment was designed to estimate nonide…
A General Method for Deriving Tight Symbolic Bounds on Causal Effects
Michael C Sachs, Gustav Jonzon, Arvid Sjölander +1
A causal query will commonly not be identifiable from observed data, in which case no estimator of the query can be contrived without further assumptions or measured variables, reg…
Causal bounds for outcome-dependent sampling in observational studies
Erin E. Gabriel, Michael C. Sachs, Arvid Sjölander
Outcome-dependent sampling designs are common in many different scientific fields including epidemiology, ecology, and economics. As with all observational studies, such designs of…
Aim for clinical utility, not just predictive accuracy
Michael C Sachs, Arvid Sjölander, Erin E Gabriel
The predictions from an accurate prognostic model can be of great interest to patients and clinicians. When predictions are reported to individuals, they may decide to take action…