Add to ORKGProviding a thorough treatment on statistical causality, this resource presents a broad collection of contributions from experts in their fields. Methods and their applications are provided with theoretical background and emphasis is given to practice rather than theory, with technical content kept to a minimum. Step-by-step instructions for using the methods are presented with a broad range of examples, including medicine, biology, economics, sociology, and political science
This review presents empirical researchers with recent advances in causal inference, and stresses th...
Traditionally, statistics has been viewed as the branch of science which deals with association. Man...
In this paper causality is seen from a pluralist point of view: About its physical reality one can n...
Providing a thorough treatment on statistical causality, this resource presents a broad collection o...
A state of the art volume on statistical causality Causality: Statistical Perspectives and Applicati...
This book compiles and presents new developments in statistical causal inference. The accompanying d...
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...
The general goal of this work is the clarification of the use of concepts of causality in medicine a...
Written by a group of well-known experts, Statistics and Causality: Methods for Applied Empirical Re...
NoCausal inference is perhaps the most important form of reasoning in the sciences. A panoply of dis...
Causality is a complex concept, which roots its developments across several fields, such as statisti...
A concise and self-contained introduction to causal inference, increasingly important in data scienc...
Many areas of political science focus on causal questions. Evidence from statistical analyses is oft...
Experiments have always been the way to study what the effect is of interventions. Causal inference ...
This review presents empirical researchers with recent advances in causal inference, and stresses th...
Traditionally, statistics has been viewed as the branch of science which deals with association. Man...
In this paper causality is seen from a pluralist point of view: About its physical reality one can n...
Providing a thorough treatment on statistical causality, this resource presents a broad collection o...
A state of the art volume on statistical causality Causality: Statistical Perspectives and Applicati...
This book compiles and presents new developments in statistical causal inference. The accompanying d...
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...
The general goal of this work is the clarification of the use of concepts of causality in medicine a...
Written by a group of well-known experts, Statistics and Causality: Methods for Applied Empirical Re...
NoCausal inference is perhaps the most important form of reasoning in the sciences. A panoply of dis...
Causality is a complex concept, which roots its developments across several fields, such as statisti...
A concise and self-contained introduction to causal inference, increasingly important in data scienc...
Many areas of political science focus on causal questions. Evidence from statistical analyses is oft...
Experiments have always been the way to study what the effect is of interventions. Causal inference ...
This review presents empirical researchers with recent advances in causal inference, and stresses th...
Traditionally, statistics has been viewed as the branch of science which deals with association. Man...
In this paper causality is seen from a pluralist point of view: About its physical reality one can n...