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Longitudinal incremental propensity score interventions for limited resource settings

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Causal inference with limited resources: proportionally-representative interventions

Mats Julius Stensrud, Aaron Leor Sarvet

Investigators often evaluate treatment effects by considering settings in which all individuals are assigned a treatment of interest, assuming that an unlimited number of treatment units are available. However, many real-life treatments are of limited supp ...

2020

Causal inference in continuous time: an example on prostate cancer therapy

Mats Julius Stensrud, Pal Christie Ryalen

In marginal structural models (MSMs), time is traditionally treated as a discrete parameter. In survival analysis on the other hand, we study processes that develop in continuous time. Therefore, Røysland (2011. A martingale approach to continuous-time mar ...

2020

In time-to-event settings, the presence of competing events complicates the definition of causal effects. Here we propose the new separable effects to study the causal effect of a treatment on an event of interest. The separable direct effect is the treatm ...

2020

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We consider the problem of learning causal models from observational data generated by linear non-Gaussian acyclic causal models with latent variables. Without considering the effect of latent variables, the inferred causal relationships among the observed ...

MICROTOME PUBL2020

A causal framework for classical statistical estimands in failure-time settings with competing events

Mats Julius Stensrud

In failure-time settings, a competing event is any event that makes it impossible for the event of interest to occur. For example, cardiovascular disease death is a competing event for prostate cancer death because an individual cannot die of prostate canc ...

2020

Partial exchangeability is sufficient for the identification of some causal effects of interest. Here we review the use of common graphical tools and the sufficient component cause model in the context of partial exchangeability. We illustrate the utility ...

2020

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Acute liver failure (ALF) or fulminant hepatitis is a rare, yet severe outcome of infection with hepatitis B virus (HBV) that carries a high mortality rate. The occurrence of a life-threatening condition upon infection with a prevalent virus in individuals ...

2019

Counting and Sampling from Markov Equivalent DAGs Using Clique Trees

Negar Kiyavash, Saber Salehkaleybar, Kun Zhang

A directed acyclic graph (DAG) is the most common graphical model for representing causal relationships among a set of variables. When restricted to using only observational data, the structure of the ground truth DAG is identifiable only up to Markov equi ...

AAAI Press2019

On the collapsibility of measures of effect in the counterfactual causal framework

Mats Julius Stensrud, Anders Huitfeldt

The relationship between collapsibility and confounding has been subject to an extensive and ongoing discussion in the methodological literature. We discuss two subtly different definitions of collapsibility, and show that by considering causal effect meas ...

2019

Can chance cause cancer? A causal consideration

Mats Julius Stensrud

The role of randomness, environment and genetics in cancer development is debated. We approach the discussion by using the potential outcomes framework for causal inference. By briefly considering the underlying assumptions, we suggest that the antagonisin ...

2017