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Using the domain-sampling model from classical test theory, the effects of measurement error on statistical tests for the difference between an obtained mean and a hypothesized mean, and the difference between two means, are demonstrated. The results indicate that lowering the reliability (i.e., increasing measurement error) of dependent variable data increases the chance of obtaining a nonsignificant result when a significant result is the correct outcome. Lowering the reliability also produces reduced estimates of strength of association.
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Richard A. Charter (1997) studied this question.
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