How humans infer causation from covariation has been the subject of a vigorous debate, most recently between the computational causal power account (P. W. Cheng, 1997) and associative learning theorists (e.g., K. Lober & D. R. Shanks, 2000). Whereas most researchers in the subject area agree that causal power as computed by the power PC theory offers a normative account of the inductive process. Lober and Shanks, among others, have questioned the empirical validity of the theory. This article offers a full report and additional analyses of the original study featured in Lober and Shanks's critique (M. J. Buehner & P. W. Cheng, 1997) and reports tests of Lober and Shanks's and other explanations of the pattern of causal judgments. Deviations...
Current models of causal induction are seriously compromised because they cannot represent variation...
Many theories of contingency learning assume (either explicitly or implicitly) that predicting wheth...
Contingency information is information about the occurrence or nonoccurrence of an effect when a pos...
How humans infer causation from covariation has been the subject of a vigorous debate, most recently...
Nearly every theory of causal induction assumes that the existence and strength of causal relations ...
This dissertation begins with a review of competing theories of human contingency judgment, and then...
The power PC theory postulates a normative procedure for making causal inferences from contingency i...
It is proposed that causal judgments about contingency information are derived from the proportion o...
The rationality of human causal judgments has been the focus of a great deal of recent research. We ...
I argue that psychologists interested in human causal judgment should understand and adopt a represe...
Much of human cognition and activity depends on causal beliefs and reasoning. In psychological resea...
According to the causal powers theory, all causal relations are understood in terms of causal powers...
In three experiments, participants made causal judgements from summary presentations of information ...
Thesis (Ph.D.)--University of Washington, 2017-03This dissertation is composed of three major compon...
The last forty years have seen an explosion of research directed at causation and causal inference. ...
Current models of causal induction are seriously compromised because they cannot represent variation...
Many theories of contingency learning assume (either explicitly or implicitly) that predicting wheth...
Contingency information is information about the occurrence or nonoccurrence of an effect when a pos...
How humans infer causation from covariation has been the subject of a vigorous debate, most recently...
Nearly every theory of causal induction assumes that the existence and strength of causal relations ...
This dissertation begins with a review of competing theories of human contingency judgment, and then...
The power PC theory postulates a normative procedure for making causal inferences from contingency i...
It is proposed that causal judgments about contingency information are derived from the proportion o...
The rationality of human causal judgments has been the focus of a great deal of recent research. We ...
I argue that psychologists interested in human causal judgment should understand and adopt a represe...
Much of human cognition and activity depends on causal beliefs and reasoning. In psychological resea...
According to the causal powers theory, all causal relations are understood in terms of causal powers...
In three experiments, participants made causal judgements from summary presentations of information ...
Thesis (Ph.D.)--University of Washington, 2017-03This dissertation is composed of three major compon...
The last forty years have seen an explosion of research directed at causation and causal inference. ...
Current models of causal induction are seriously compromised because they cannot represent variation...
Many theories of contingency learning assume (either explicitly or implicitly) that predicting wheth...
Contingency information is information about the occurrence or nonoccurrence of an effect when a pos...