3 ms·
Looking just at the "equals" data still looks weird (although in a different way): require(tidypvals) allp = allp[!allp$pvalue > 1,] allp_eq = allp
by nonbel 9y ago
Looking just at the "equals" data still looks weird (although in a different way):
require(tidypvals)
allp = allp[!allp$pvalue > 1,]
allp_eq = allp[allp$operator == "equals", ]
hist(allp_eq$pvalue, xlim = c(0, .15), breaks = 1000)
https://image.ibb.co/i2aBqQ/pvalue_equals.png https://image.ibb.co/i2aBqQ/pvalue_equals.png
- Mathnerd314 9y agoThose look like rounding artifacts; the pic I posted just used some Gaussian smoothing, but there are (way more complex) methods for handling them correctly: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2847785/ https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2847785/ The overall function is a p-curve, here's a paper on it: http://journals.sagepub.com/doi/pdf/10.1177/1745691614553988 http://journals.sagepub.com/doi/pdf/10.1177/1745691614553988
- nonbel 9y agoYep, rounding would make sense here. I have to agree that this data is showing much less than at first appears.