In their article, Vul, Harris, Winkielman, and Pashler (2009), (this issue) raise the issue of nonindependent analysis in behavioral neuroimaging, whereby correlations are artificially inflated as a result of spurious statistical procedures. In this comment, I note that the phenomenon in question is a type of selection bias and hence is neither new nor unique to fMRI. The use of massive, complex data sets (common in modern applications) to answer increasingly intricate scientific questions presents many potential pitfalls to valid statistical analysis. Strong collaboration between statisticians and scientists and the development of statistical methods specific to the types of data encountered in practice can help researchers avoid these pitfalls.
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