Concept

Modèle causal de Neyman-Rubin

Publications associées (53)

Health effects of power plant emissions through ambient air quality

Coal burning power plants are a frequent target of regulatory programmes because of their emission of chemicals that are known precursors to the formation of ambient particulate air pollution. Health impact assessments of emissions from coal power plants t ...

2020

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

The additive hazard estimator is consistent for continuous-time marginal structural models

Mats Julius Stensrud, Pal Christie Ryalen

Marginal structural models (MSMs) allow for causal analysis of longitudinal data. The standard MSM is based on discrete time models, but the continuous-time MSM is a conceptually appealing alternative for survival analysis. In applied analyses, it is often ...

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

Effect heterogeneity and variable selection for standardizing causal effects to a target population

Mats Julius Stensrud, Anders Huitfeldt

The participants in randomized trials and other studies used for causal inference are often not representative of the populations seen by clinical decision-makers. To account for differences between populations, researchers may consider standardizing resul ...

2019

Feedback and Mediation in Causal Inference Illustrated by Stochastic Process Models

Mats Julius Stensrud

The concept of causality is naturally related to processes developing over time. Central ideas of causal inference like time-dependent confounding (feedback) and mediation should be viewed as dynamic concepts. We shall study these concepts in the context o ...

2018

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

Exploring Selection Bias by Causal Frailty Models

Mats Julius Stensrud

Counter-intuitive associations appear frequently in epidemiology, and these results are often debated. In particular, several scenarios are characterized by a general risk factor that appears protective in particular subpopulations, for example, individual ...

2017

A Bayesian view of doubly robust causal inference

In causal inference the effect of confounding may be controlled using regression adjustment in an outcome model, propensity score adjustment, inverse probability of treatment weighting or a combination of these. Approaches based on modelling the treatment ...

Oxford University Press2016

The multisensory function of the human primary visual cortex

Roberto Martuzzi, Antonia Thelen

It has been nearly 10 years since Ghazanfar and Schroeder (2006) proposed that the neocortex is essentially multisensory in nature. However, it is only recently that sufficient and hard evidence that supports this proposal has accrued. We review evidence t ...

Pergamon-Elsevier Science Ltd2016

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