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11/19 vs 8/25 gives p=.09 for a two-tailed test, I think. Is that really worth publishing?
by drc500free 4y ago
11/19 vs 8/25 gives p=.09 for a two-tailed test, I think.
Is that really worth publishing?
- isoprophlex 4y agoYes. Two tailed test gives p=0.0854 Do enough random microscopy on enough cemetaries and you have a tale to tell every time. I'm not really convinced there's an actual story here.
- pacaro 4y agoThe low sample sizes jumped out at me too. The article is low quality in plenty of other ways too.
- kuhewa 4y agoYou have to look at it in the context of the field, ~25-30 ish grave soil samples under fairly controlled conditions (e.g., burials in each group within about a km of each other, control soil samples taken from each grave, similar time period) ain't bad for paleo-helminthology. Sure, it leaves uncertainty in terms of conclusions but 'low quality' is a bit much.
- pacaro 4y agoLate response. I'm inclined to believe that the original paper, and the work done by the archeologists etc. is of the highest standard. The article itself was quite poorly written
- kuhewa 4y agoBarnard's test gave p < 0.05. But sure, do enough fine-scale examination of Medieval graves and you will find something interesting. That's kinda the point of archaeology/anthropology.
- deleted 4y ago[deleted]
- niemandhier 4y agoIt is, when you prior is that the populations should be different with a difference in the opposite direction. But even than the magnitude of the observed effect is so noisy ( large type m error)
- ogogmad 4y agoGood catch! I'm more inclined to use a Bayesian approach here because we can't be certain about the probability of either population becoming infected. The 80% Credible Intervals for the two Beta distributions overlap: [1] and [2]. So indeed, the chance that either a monk or a normal villager would get infected by a parasite could be about the same. I'm not sure if using Credible Intervals in this way is kosher, so someone feel free to critique. Ideally, if p is the unknown probability of a villager getting infected, and q is the unknown probability of a monk getting infected, then we need the posterior distribution of p-q. We have all the data needed to estimate this; you may use either simulations or characteristic functions to do it. [1] - https://www.wolframalpha.com/input?i=Beta%2812%2C9%29+distribution https://www.wolframalpha.com/input?i=Beta%2812%2C9%29+distri... [2] - https://www.wolframalpha.com/input?i=Beta%289%2C18%29+distribution https://www.wolframalpha.com/input?i=Beta%289%2C18%29+distri...
- ogogmad 4y agoI just realised the OP probably used a Fisher test or something like it. The Bayesian approach isn't necessarily better then.
- drc500free 4y agoMy stats are pretty rusty, I checked if the two binomial distributions were different. No idea if that reduces down to a Fisher test!
- kuhewa 4y agoBarnards, which isn't as conservative as Fisher's exact. My understanding is Fisher's would be necessary if the number of positive cases was constrained (not applicable to this kind of work really but e.g. 600 years ago someone had ten eggs and distributed amongst the laypeople and the friars).
- kuhewa 4y agoBarnard's test is appropriate here, because while the experimental design is a 2-way contingency table, only the columns (# villagers and # friars) are constrained, the rows (# infected/ # not infected) are not. P value was just under 0.05.