However, this corresponds to a general pattern of causal relationships: observations on a common consequence of two independent causes tend to render those causes dependent, because information about one of the causes tends to make the other more or less likely, given that the consequence has occurred. This pattern is known as selection bias or Berkson's paradox in the statistical literature (Berkson 1946) and as the explaining away effect in artificial intelligence. (Kim and Pearl 1983)引自 1. Introduction to probabilities, graphs, and causal models;
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