False Discovery Rate
False Discovery Rate (FDR) is a statistical procedure employed to correct for multiple comparisons. Development was initially motivated in part as an alternative to the use of conservative familywise error rate (FWER) corrections that failed to identify marked effects in high-dimensional datasets that contained few cases (see Benjamini and Hochberg 1995). The False Discovery Rate is defined as the expected proportion of errors committed by falsely rejecting the null hypothesis (Benjamini and Hochberg 1995; Lin and Lee 2015). While originally implemented in behavioral genetics research (Benjamini et al. 2001; Goeman and Solari 2014), it has recently been introduced to the neuroimaging literature as an alternative to popular...
References and Readings
- Benjamini, Y., & Hochberg, Y. (1995). Controlling the false discovery rate: A practical and powerful approach to multiple testing. Journal of the Royal Statistical Society. Series B (Methodological), 57(1), 289–300.Google Scholar