How persuasive is a good fit? A comment on theory testing
How persuasive is a good fit? A comment on theory testing
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DOI：
10.1037/0033-295x.107.2.358
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发表时间：
2000-04-01
影响因子：
5.4
通讯作者：
Pashler, H
中科院分区：
文献类型：
--
作者：
Roberts, S;Pashler, H
具有自由参数的定量理论在与数据紧密拟合时往往获得信任。这是一个错误。良好的拟合并没有揭示理论的灵活性（它不能拟合的程度），数据的可变性（数据排除理论不能拟合的程度有多坚定），或者其他结果的可能性（也许理论可以拟合任何看似合理的结果），读者需要所有这3条信息来决定拟合应该在多大程度上增加对理论的信任。科学哲学家和心理学历史都不支持将契合度作为证据；似乎没有一个主要由良好匹配支持的理论导致了明显的进步的例子。检验一个有自由参数的理论的一个更好的方法是确定理论如何约束可能的结果（即，它预测了什么），评估实际结果与这些约束的一致程度，并确定可能的替代结果是否与理论不一致，考虑到数据的可变性。
Quantitative theories with free parameters often gain credence when they closely fit data. This is a mistake. A good fit reveals nothing about the flexibility of the theory (how much it cannot fit), the variability of the data (how firmly the data rule out what the theory cannot fit), or the likelihood of other outcomes (perhaps the theory could have fit any plausible result), and a reader needs all 3 pieces of information to decide how much the fit should increase belief in the theory. The use of good fits as evidence is not supported by philosophers of science nor by the history of psychology; there seem to be no examples of a theory supported mainly by good fits that has led to demonstrable progress. A better way to test a theory with free parameters is to determine how the theory constrains possible outcomes (i.e., what it predicts), assess how firmly actual outcomes agree with those constraints, and determine if plausible alternative outcomes would have been inconsistent with the theory, allowing for the variability of the data.