Using false discovery rates for multiple comparisons in ecology and evolution
By Nathan Pike. 2011
595 citations recorded by the source corpus.
Subfields: Artificial Intelligence, Statistics and Probability
View Paper: https://www.semanticscholar.org/paper/674a98ecf91313cc7c50c6908de3756e87145593
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In Artificial Intelligence
In Statistics and Probability
Citations in the corpus
- Flight response of slope‐soaring birds to seasonal variation in thermal generation (2015, unknown): “We accounted for multiple comparisons within models using false discovery rates (Benjamini & Hochberg 1995; Garc ıa 2004; Pike 2011).”
- Are there differences between behavioral measurement methods? A comparison of the predictive validity of two ratings methods in a working dog program (2012, unknown): “Due to the large number of comparisons (Pike, 2011) and large sample size (Yoccoz, 1991) for this analysis, we emphasized interpretation of correlation coefficients as weak/not different from zero (0.”
- Old‐growth forests buffer climate‐sensitive bird populations from warming (2018, methodology): “Therefore, we used a false discovery rate (FDR) procedure (the “graphically sharpened method” [Pike, 2011]) which does not suffer from the same loss of power but corrects for multiple comparisons across species.”