Add to ORKGAbstract. This talk describes the theory of causal inference in randomized experiments and nonrandomized observational studies, using two simple theo-retical/actual examples for illustration. Key ideas: causal effects, randomized experiments, adjustments for observed covariates, sensitivity analysis for un-observed covariates, reducing sensitivity to hidden bias using design strategies
This manuscript includes three topics in causal inference, all of which are under the randomization ...
With increasing data availability, treatment causal effects can be evaluated across different datase...
The randomized controlled trial is widely recognized as the epidemiologic "gold standard "...
Abstract. This talk describes the theory of causal inference in randomized experiments and nonrandom...
In observational studies, identifying assumptions may fail, often quietly and without notice, leadin...
This dissertation explores methodological topics in the analysis of randomized experiments, with a f...
For estimating causal effects of treatments, randomized experiments are generally considered the gol...
Observational studies aiming to estimate causal effects often rely on conceptual frameworks that are...
In the daily news and the scientific literature, we are faced with conflicting claims about the effe...
For obtaining causal inferences that are objective, and therefore have the best chance of revealing ...
The Working Paper gives an overview about the topic of causal inference,covered in the Institute on ...
Experiments have always been the way to study what the effect is of interventions. Causal inference ...
We attempt to clarify, and suggest how to avoid, several serious misunderstandings about and fal-lac...
Indirect experiments are studies in which randomized control is replaced by randomized encouragement...
Causal inferences in experimental studies and observational studies have common empirical philosophi...
This manuscript includes three topics in causal inference, all of which are under the randomization ...
With increasing data availability, treatment causal effects can be evaluated across different datase...
The randomized controlled trial is widely recognized as the epidemiologic "gold standard "...
Abstract. This talk describes the theory of causal inference in randomized experiments and nonrandom...
In observational studies, identifying assumptions may fail, often quietly and without notice, leadin...
This dissertation explores methodological topics in the analysis of randomized experiments, with a f...
For estimating causal effects of treatments, randomized experiments are generally considered the gol...
Observational studies aiming to estimate causal effects often rely on conceptual frameworks that are...
In the daily news and the scientific literature, we are faced with conflicting claims about the effe...
For obtaining causal inferences that are objective, and therefore have the best chance of revealing ...
The Working Paper gives an overview about the topic of causal inference,covered in the Institute on ...
Experiments have always been the way to study what the effect is of interventions. Causal inference ...
We attempt to clarify, and suggest how to avoid, several serious misunderstandings about and fal-lac...
Indirect experiments are studies in which randomized control is replaced by randomized encouragement...
Causal inferences in experimental studies and observational studies have common empirical philosophi...
This manuscript includes three topics in causal inference, all of which are under the randomization ...
With increasing data availability, treatment causal effects can be evaluated across different datase...
The randomized controlled trial is widely recognized as the epidemiologic "gold standard "...