Add to ORKGThe randomized controlled trial is widely recognized as the epidemiologic "gold standard " for causality inferences (1, 2). Random assignment of study subjects of-fers the best chance of forming groups that tend to be similar in all respects, except for the exposure or treatment under study. (Al-though treatment usually refers to a clinical intervention and exposure to an environ-mental agent (e.g., air pollutant) or self-imposed maneuver (e.g., cigarette smok-ing), we shall use the two terms inter-changeably.) There are, however, many barriers to the use of controlled trials (3-7). Some exposures simply cannot be as-signed. Examples include such factors as
Abstract. This talk describes the theory of causal inference in randomized experiments and nonrandom...
For obtaining causal inferences that are objective, and therefore have the best chance of revealing ...
With increasing data availability, causal effects can be evaluated across different data sets, both ...
For estimating causal effects of treatments, randomized experiments are generally considered the gol...
Background Applications of causal inference methods to randomised controlled trial (RCT) data have u...
In the daily news and the scientific literature, we are faced with conflicting claims about the effe...
International audienceCase-control and cohort studies are the two principal types of observational s...
In observational studies, identifying assumptions may fail, often quietly and without notice, leadin...
In observational studies, identifying assumptions may fail, often quietly and without notice, leadin...
Background: In clinical medical research. causality is demonstrated by randomized controlled trials ...
Abstract. This talk describes the theory of causal inference in randomized experiments and nonrandom...
Estimating the causal effect of some exposure on some outcome is the goal of many epidemiological st...
Background: Increasingly, risk of bias tools are used to evaluate epidemiologic studies as part of e...
Background: Increasingly, risk of bias tools are used to evaluate epidemiologic studies as part of e...
Background: Increasingly, risk of bias tools are used to evaluate epidemiologic studies as part of e...
Abstract. This talk describes the theory of causal inference in randomized experiments and nonrandom...
For obtaining causal inferences that are objective, and therefore have the best chance of revealing ...
With increasing data availability, causal effects can be evaluated across different data sets, both ...
For estimating causal effects of treatments, randomized experiments are generally considered the gol...
Background Applications of causal inference methods to randomised controlled trial (RCT) data have u...
In the daily news and the scientific literature, we are faced with conflicting claims about the effe...
International audienceCase-control and cohort studies are the two principal types of observational s...
In observational studies, identifying assumptions may fail, often quietly and without notice, leadin...
In observational studies, identifying assumptions may fail, often quietly and without notice, leadin...
Background: In clinical medical research. causality is demonstrated by randomized controlled trials ...
Abstract. This talk describes the theory of causal inference in randomized experiments and nonrandom...
Estimating the causal effect of some exposure on some outcome is the goal of many epidemiological st...
Background: Increasingly, risk of bias tools are used to evaluate epidemiologic studies as part of e...
Background: Increasingly, risk of bias tools are used to evaluate epidemiologic studies as part of e...
Background: Increasingly, risk of bias tools are used to evaluate epidemiologic studies as part of e...
Abstract. This talk describes the theory of causal inference in randomized experiments and nonrandom...
For obtaining causal inferences that are objective, and therefore have the best chance of revealing ...
With increasing data availability, causal effects can be evaluated across different data sets, both ...