Add to ORKGA state of the art volume on statistical causality Causality: Statistical Perspectives and Applications presents a wide-ranging collection of seminal contributions by renowned experts in the field, providing a thorough treatment of all aspects of statistical causality. It covers the various formalisms in current use, methods for applying them to specific problems, and the special requirements of a range of examples from medicine, biology and economics to political science. This book:Provides a clear account and comparison of formal languages, concepts and models for statistical causality. Add
This paper summarizes recent advances in causal inference and underscores the paradigmatic shifts th...
In this paper causality is seen from a pluralist point of view: About its physical reality one can n...
This review presents empirical researchers with recent advances in causal inference, and stresses th...
Providing a thorough treatment on statistical causality, this resource presents a broad collection o...
Providing a thorough treatment on statistical causality, this resource presents a broad collection o...
Causal inference is perhaps the most important form of reasoning in the sciences. A panoply of disci...
There is a need for integrated thinking about causality, probability and mechanisms in scientific me...
This book compiles and presents new developments in statistical causal inference. The accompanying d...
NoCausal inference is perhaps the most important form of reasoning in the sciences. A panoply of dis...
Written by a group of well-known experts, Statistics and Causality: Methods for Applied Empirical Re...
The general goal of this work is the clarification of the use of concepts of causality in medicine a...
A concise and self-contained introduction to causal inference, increasingly important in data scienc...
This paper summarizes recent advances in causal inference and underscores the paradigmatic shifts th...
This review presents empirical researchers with recent advances in causal inference, and stresses th...
This paper summarizes recent advances in causal inference and underscores the paradigmatic shifts th...
This paper summarizes recent advances in causal inference and underscores the paradigmatic shifts th...
In this paper causality is seen from a pluralist point of view: About its physical reality one can n...
This review presents empirical researchers with recent advances in causal inference, and stresses th...
Providing a thorough treatment on statistical causality, this resource presents a broad collection o...
Providing a thorough treatment on statistical causality, this resource presents a broad collection o...
Causal inference is perhaps the most important form of reasoning in the sciences. A panoply of disci...
There is a need for integrated thinking about causality, probability and mechanisms in scientific me...
This book compiles and presents new developments in statistical causal inference. The accompanying d...
NoCausal inference is perhaps the most important form of reasoning in the sciences. A panoply of dis...
Written by a group of well-known experts, Statistics and Causality: Methods for Applied Empirical Re...
The general goal of this work is the clarification of the use of concepts of causality in medicine a...
A concise and self-contained introduction to causal inference, increasingly important in data scienc...
This paper summarizes recent advances in causal inference and underscores the paradigmatic shifts th...
This review presents empirical researchers with recent advances in causal inference, and stresses th...
This paper summarizes recent advances in causal inference and underscores the paradigmatic shifts th...
This paper summarizes recent advances in causal inference and underscores the paradigmatic shifts th...
In this paper causality is seen from a pluralist point of view: About its physical reality one can n...
This review presents empirical researchers with recent advances in causal inference, and stresses th...