Abstract
Using an elementary form of a Monte Carlo experiment, this paper illustrates a common error that arises when efforts are made to substantively interpret experimental outcomes that are not found to be statistically significant. It also relates these ideas to misinterpretations of data arising through regression artifacts. The purpose of this review is to identify certain misuses of information in the assessment of experimental and quasi-experimental evaluations of therapeutic treatments.
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