One of the more challenging issues in epidemiological research is being able to provide an unbiased estimate of the causal exposure-disease effect, to assess the possible etiological mechanisms and the implication for public health. A major source of bias is confounding, which can spuriously create or mask the causal relationship. In the last ten years, methodological research has been developed to better de_ne the concept of causation in epidemiology and some important achievements have resulted in new statistical models. In this review, we aim to show how a technique the well known by statisticians, i.e. standardization, can be seen as a method to estimate causal e_ects, equivalent under certain conditions to the inverse probability treat...
The past few decades have witnessed rapid and unprecedented theoretical progress on the science of c...
The past few decades have witnessed rapid and unprecedented theoretical progress on the science of c...
This chapter explores the idea that causal inference is warranted if and only if the mechanism under...
One of the more challenging issues in epidemiological research is being able to provide an unbiased ...
Traditionally, statistics has been viewed as the branch of science which deals with association. Man...
In ideal randomised experiments, association is causation: association measures can be interpreted a...
Causal inference methods are statistical techniques used to analyse the causal effect of a treatment...
This book compiles and presents new developments in statistical causal inference. The accompanying d...
Inferring causality is necessary to achieve the goal of epidemiology, which is to elucidate the caus...
Experiments have always been the way to study what the effect is of interventions. Causal inference ...
Population health researchers from different fields often address similar substantive questions but ...
This chapter explores the idea that causal inference is warranted if and only if the mechanism under...
This chapter explores the idea that causal inference is warranted if and only if the mechanism under...
This chapter explores the idea that causal inference is warranted if and only if the mechanism under...
Estimating the causal effect of some exposure on some outcome is the goal of many epidemiological st...
The past few decades have witnessed rapid and unprecedented theoretical progress on the science of c...
The past few decades have witnessed rapid and unprecedented theoretical progress on the science of c...
This chapter explores the idea that causal inference is warranted if and only if the mechanism under...
One of the more challenging issues in epidemiological research is being able to provide an unbiased ...
Traditionally, statistics has been viewed as the branch of science which deals with association. Man...
In ideal randomised experiments, association is causation: association measures can be interpreted a...
Causal inference methods are statistical techniques used to analyse the causal effect of a treatment...
This book compiles and presents new developments in statistical causal inference. The accompanying d...
Inferring causality is necessary to achieve the goal of epidemiology, which is to elucidate the caus...
Experiments have always been the way to study what the effect is of interventions. Causal inference ...
Population health researchers from different fields often address similar substantive questions but ...
This chapter explores the idea that causal inference is warranted if and only if the mechanism under...
This chapter explores the idea that causal inference is warranted if and only if the mechanism under...
This chapter explores the idea that causal inference is warranted if and only if the mechanism under...
Estimating the causal effect of some exposure on some outcome is the goal of many epidemiological st...
The past few decades have witnessed rapid and unprecedented theoretical progress on the science of c...
The past few decades have witnessed rapid and unprecedented theoretical progress on the science of c...
This chapter explores the idea that causal inference is warranted if and only if the mechanism under...