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结构的性质与发现AI 解读

Extending principles of experimentation, we discuss conditions under which nonexperimental data allow consistent estimation of effects of the kind revealed by experimentation and relevant to decisions. We show how implications of these conditions are often overlooked and how failure to distinguish between “factors” and “concomitants” makes almost anything said about a model ambiguous if not wrong. The effects to be estimated dictate the factors to be included; consistency…

论结构的本质与发现AI 解读

Extending principles of experimentation, we discuss conditions under which nonexperimental data allow consistent estimation of effects of the kind revealed by experimentation and relevant to decisions. We show how implications of these conditions are often overlooked and how failure to distinguish between “factors” and “concomitants” makes almost anything said about a model ambiguous if not wrong. The effects to be estimated dictate the factors to be included; consistency…