This article seeks to describe complex events (often occurring at low frequency) where standard statistical modeling of causality is not likely to prove feasible. Such events are perhaps best analyzed using the method of comparative narratives, which relies on an internal model of causality
Traditionally, social scientists perceived causality as regularity. As a consequence, qualitative co...
Counterfactual analysis has a long and distinguished history in comparative research. To some, count...
Abstract A possible defect in a paradigm often used in making causal inference is noted. The defect ...
This article seeks to describe complex events (often occurring at low frequency) where standard stat...
The article explores the logic of the orthodox statistical model of causal inference, where many obs...
When case studies are constructed as narratives, then causal explanation can be achieved without eit...
When case studies are constructed as narratives, then causal explanation can be achieved without eit...
International audienceAscribing causality amounts to determining what elements in a sequence of repo...
Ascribing causality amounts to determining what elements in a sequence of reported facts can be rela...
[Extract] Causal explanations can help us understand why events change course, and why the world tur...
There is little consensus regarding the circumstances in which people spontaneously generate causal ...
Counterfactual theories of causal judgment propose that people infer causality between events by com...
Contingency information is information about empirical associations between possible causes and outc...
A widely agreed upon definition of time series causality inference, established in the sem-inal 1969...
Multiple metrics have been developed to detect causality relations between data describing the eleme...
Traditionally, social scientists perceived causality as regularity. As a consequence, qualitative co...
Counterfactual analysis has a long and distinguished history in comparative research. To some, count...
Abstract A possible defect in a paradigm often used in making causal inference is noted. The defect ...
This article seeks to describe complex events (often occurring at low frequency) where standard stat...
The article explores the logic of the orthodox statistical model of causal inference, where many obs...
When case studies are constructed as narratives, then causal explanation can be achieved without eit...
When case studies are constructed as narratives, then causal explanation can be achieved without eit...
International audienceAscribing causality amounts to determining what elements in a sequence of repo...
Ascribing causality amounts to determining what elements in a sequence of reported facts can be rela...
[Extract] Causal explanations can help us understand why events change course, and why the world tur...
There is little consensus regarding the circumstances in which people spontaneously generate causal ...
Counterfactual theories of causal judgment propose that people infer causality between events by com...
Contingency information is information about empirical associations between possible causes and outc...
A widely agreed upon definition of time series causality inference, established in the sem-inal 1969...
Multiple metrics have been developed to detect causality relations between data describing the eleme...
Traditionally, social scientists perceived causality as regularity. As a consequence, qualitative co...
Counterfactual analysis has a long and distinguished history in comparative research. To some, count...
Abstract A possible defect in a paradigm often used in making causal inference is noted. The defect ...
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