![]() ![]() A couple days ago, Michaela DeBolt ( alerted me to a new paper by Hedge et al. This is also true for reaction time (RT) data. ![]() It turns out that ordinary measures of reliability are quite unsatisfactory for assessing whether ERP data are noisy. I’ve been thinking about this issue for several years in the context of ERP data quality (leading to this paper). And it also turns out that, although reliability is extremely important in some types of research (e.g., correlational studies of individual differences), it’s the wrong way to think about data quality when you are comparing groups or conditions (e.g., using t tests or ANOVAs). It is commonly said that “a measure cannot be valid if it is not reliable.” It turns out that this is simply false (as long as we define these terms in the traditional way). ![]()
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